Rigor in science and science reporting: updated guidelines for submissions to Molecular Autism
Bibliographic record
Abstract
There was some controversial press reporting of an article published in Molecular Autism by Anwar et al. [1].In addition, at least two organizations dedicated to scientific accuracy in reporting have commented on this article, including www.sciencemediacentre.org and www.healthnewsreview.org.While the authors expressed some of the caveats of the study in their article, the subsequent reporting in the press and non-specialist community omitted critical caveats and we feel compelled to alter our guidelines to better address such issues.A particular concern is claims about a biological test being diagnostic.Countless publications have made the point that what is observed in a selected sample of cases and controls is very far from being a diagnostic test.Drs.Paul Meehl and Albert Rosen summarized many of the relevant issues as early as 1955 [2], in response to a 1954 white paper by the American Psychological Association [3].In summary, findings of even very significant differences in a given measure between cases versus controls are not by themselves sufficient to support the use of such a measure for diagnosis.This is especially true for rare events because for "any attempt at prediction of infrequent behavior, a large number of false positives are
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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 | 0.336 | 0.680 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.032 | 0.013 |
| Open science | 0.015 | 0.008 |
| Research integrity | 0.041 | 0.048 |
| Insufficient payload (model declined to judge) | 0.015 | 0.025 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".