Entering the MATRICS: the adverse effects of CBT-I on neurocognitive functioning in COMISA individuals
Bibliographic record
Abstract
Journal Article Entering the MATRICS: the adverse effects of CBT-I on neurocognitive functioning in COMISA individuals Get access Célyne H Bastien, Célyne H Bastien School of Psychology, Université Laval, Québec, Canada Corresponding author. Célyne H. Bastien, School of Psychology, Université Laval, Quebec G1V0A6, Canada. Email: Celyne.bastien@psy.ulaval.ca. https://orcid.org/0000-0002-9236-9125 Search for other works by this author on: Oxford Academic Google Scholar Jason G Ellis, Jason G Ellis Department of Psychology, Northumbria University, Newcastle-upon-Tyne, UK https://orcid.org/0000-0002-8496-520X Search for other works by this author on: Oxford Academic Google Scholar Michael L Perlis Michael L Perlis Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA Search for other works by this author on: Oxford Academic Google Scholar Sleep, Volume 46, Issue 8, August 2023, zsad164, https://doi.org/10.1093/sleep/zsad164 Published: 06 June 2023 Article history Published: 06 June 2023 Corrected and typeset: 14 July 2023
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".