Additional file 2 of Fear response-based prediction for stress susceptibility to PTSD-like phenotypes
Bibliographic record
Abstract
Additional file 2: Supplemental Fig. 2. Anxious behaviors do not correlate with occurrence of PTSD-like phenotypes. (A) Anxiety levels of stressed mice do not correlate with PTSD-like behaviors. Neither the amount of time that stressed mice spent in the open arms of the EPM (top left, Pearson correlations, R = − 0.03426) nor the number of entries that stressed mice made into open arms (bottom left, R = − 0.01298) correlated with the fear generalization indices. Neither the amount of time that stressed mice spent in the open arms of the EPM (top right, R = − 0.01298) nor the number of entries that stressed mice made into open arms (bottom right, R = 0.06744) correlated with freezing responses 24 h after memory extinction. (B) Anxiety levels of unstressed control mice do not correlate with PTSD-like behaviors. Neither the amount of time that control mice spent in the open arms of the EPM (top left, R = − 0.09436) nor the number of entries that control mice made into open arms (bottom left, R = 0.09593) correlated with the fear generalization indices. Neither the amount of time that control mice spent in the open arms of the EPM (top right, R = − 0.2067) nor the number of entries that stressed mice made into open arms (bottom right, R = 0.09174) correlated with freezing responses 24 h after memory extinction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.844 | 0.149 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".