Implementation of the CBAM-based algorithm for Source Device Identification (SDI) leveraging Grad-CAM explanations
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Updated
Sep 27, 2025 - Python
Implementation of the CBAM-based algorithm for Source Device Identification (SDI) leveraging Grad-CAM explanations
v5: Five-cell parallel constraint-reasoning experiment on Claude Haiku 4.5. Phase D closed with a 4-tier representational hierarchy as the headline finding (4/5 cells significant past Bonferroni). See STATUS.md / MEMO.md.
Python implementation of the McNemar's mid-p statistical significance test.
Decide whether an eval delta is a real regression or sampling noise.
McNemar's paired test for NLP model comparison. Exact binomial fallback when b+c < 25. Single-file, runs in browser.
Empirical study of what determines IMDB test accuracy under frozen GloVe + shallow neural head or linear baseline: architecture (SNN/CNN/LSTM), sequence length, padding masking, EarlyStopping, and threshold tuning. A TF-IDF + logistic regression baseline beats every neural condition. Reanalysis of a 2022 project.
Wilson confidence intervals, difference of proportions, and McNemar's test for LLM evaluation results. Client-side, single file.
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