Bibliographic record
Abstract
W dniu 08.07.2015 w czasopiśmie British Medical Journal opublikowany został artykuł „Specific SSRI and birth defects : bayesian analysis to interpret new data in the context of previous reports”, autorstwa J. Reefhuis, (National Center on Birth Defects and Developmetal Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, USA); O. Devine (National Center on Birth Defects and Developmetal Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, USA); JM Friedman (Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada); C. Louik (Slone Epidemiology Center at Boston University, Boston, MA, USA) oraz MA. Honein (National Center on Birth Defects and Developmetal Disabilities, Centers for Disease Control and Prevention, Atlanta, GA, USA), zawierający nowe, istotne dane dotyczące farmakoterapii depresji w okresie ciąży. Celem artykułu była ocena bezpieczeństwa stosowania w pierwszym trymestrze ciąży pięciu leków przeciwdepresyjnych z grupy wybiórczych inhibitorów wychwytu zwrotnego serotoniny (SSRI- selective serotonine reuptake inhibitors), tj. fluoksetyny, sertraliny, paroksetyny, citalopramu oraz escitalopramu.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.019 | 0.018 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".