From 19dce87b60e6208429ed4b438755cb80ff34c7bd Mon Sep 17 00:00:00 2001 From: Verlyn Date: Thu, 16 Jul 2026 14:03:17 -0500 Subject: [PATCH] docs(preregistrations): add calibration statistical analysis plan --- docs/preregistrations/calibration-sap.md | 62 ++++++++++++++++++++++++ 1 file changed, 62 insertions(+) create mode 100644 docs/preregistrations/calibration-sap.md diff --git a/docs/preregistrations/calibration-sap.md b/docs/preregistrations/calibration-sap.md new file mode 100644 index 0000000..260640d --- /dev/null +++ b/docs/preregistrations/calibration-sap.md @@ -0,0 +1,62 @@ +# Calibration Statistical Analysis Plan (SAP) + +## 1. Metadata +- **Title**: Phase 12 Lane A Instrument Calibration Preregistration +- **Date**: 2026-07-16 +- **Version**: 1.0.0 +- **Status**: Preregistered Draft + +--- + +## 2. E4 Grader Validation Protocol +The objective of E4 is to measure the agreement between the deterministic machine grader ($G_m$) and the independent human gold label ($G_h$). + +### Metrics +We will compute the following metrics over a class-balanced validation corpus ($N \ge 40$ attempts representing all four classes and failure modes): + +* **Sensitivity (True Positive Rate)**: + $$\text{Sensitivity} = \frac{TP}{TP + FN}$$ + *Where $TP$ is the number of attempts graded as success by both human and machine, and $FN$ is the number of attempts graded as success by human but failure by machine.* + +* **Specificity (True Negative Rate)**: + $$\text{Specificity} = \frac{TN}{TN + FP}$$ + *Where $TN$ is graded as failure by both, and $FP$ is graded as failure by human but success by machine.* + +* **Positive Predictive Value (PPV)**: + $$\text{PPV} = \frac{TP}{TP + FP}$$ + +* **Negative Predictive Value (NPV)**: + $$\text{NPV} = \frac{TN}{TN + FN}$$ + +### Validation Thresholds +The instrument is declared valid for calibration only if: +* $\text{Sensitivity} \ge 0.90$ +* $\text{Specificity} \ge 0.95$ + +--- + +## 3. E1 A/A Independence Study +The objective of E1 is to estimate the within-session correlation coefficient ($\rho$) and verify that local hardware and cache conditions do not introduce systematic bias between experimental arms. + +### Design +* **Arms**: Arm 1 (A) and Arm 2 (A') run identical model digests (`qwen3.5:9b`). +* **Sample Size**: 3 serial replicates of the frozen 40-task suite per arm (240 total attempts). +* **Null Hypothesis**: $H_0: \rho = 0$ (attempts are independent). +* **Test Statistic**: Pearson correlation coefficient and Ljung-Box test for serial autocorrelation on latency and success vectors. + +--- + +## 4. E2 Operating Characteristics Simulation +E2 evaluates the provisional decision rule and estimates statistical power under varying effect sizes. + +### Simulation Inputs +* Empirical success rates and transition matrices from E1. +* Measurement error rates from E4. +* Simulation runs ($B = 10,000$) to evaluate the Type I error rate ($\alpha$) and statistical power ($1-\beta$) under candidate sample sizes ($N$) and Minimum Practical Improvement Boundaries (MPIB). + +--- + +## 5. Attrition & Missingness Handling +Every initiated attempt must be accounted for in the attrition table. +* **Timeout/OOM/Harness Error**: Evaluated as `NOT_EVALUABLE` and excluded from the capability pass-rate calculations, but documented in the attrition table. +* **Transient Network Error**: Subject to a maximum of 1 automatic retry; the retry carries its own unique attempt index and receipts.