Bibliographic record
Abstract
studies) [12].Currently I have the privilege of participating in an interdisciplinary research consortium on stress, self-control and addiction (http://stress.yale.edu/and http://stress.yale.edu/projects.html).The consortium includes 14 coordinated and integrated research projects that involve rats, non-human primates and humans and use molecular/cellular, genetic, brain imaging, behavioral, clinical and epidemiological approaches.While there exist organizational and logistical challenges in conducting interdisciplinary team science, such an approach holds significant promise for understanding complex neuropsychiatric conditions such as addiction that are currently frequently refractory to existing treatments [13].Even if such studies do not identify the cause of addiction [14], they have tremendous potential for generating significant advances in prevention and treatment strategies and reducing the suffering and societal burden associated currently with addictions.AA017539, P50 DA09241, P50 DA016556, R37 DA15969, P01 DA022446 and UL1 DE19586,
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.031 |
| Scholarly communication | 0.007 | 0.022 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.011 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".