Reviewing the reviewers: the quality of reporting in three secondary journals.
Bibliographic record
Abstract
BACKGROUND: Secondary journals such as ACP Journal Club (ACP), Journal Watch (JW) and Internal Medicine Alert (IMA) have enormous potential to help clinicians remain up to date with medical knowledge. However, for clinicians to evaluate the validity and applicability of new findings, they need information on the study design, methodology and results. METHODS: Beginning with the first issue in March 1997, we selected 50 consecutive summaries of studies addressing therapy or prevention and internal medicine content from each of the ACP, JW and IMA. We evaluated the summaries for completeness of reporting key aspects of study design, methodology and results. RESULTS: All of the summaries in ACP reported study design, as compared with 72% of the summaries in JW and IMA (p < 0.001). In summaries of randomized controlled trials the 3 secondary journals were similar in reporting concealment of patient allocation (none reported this), blinding status of participants (ACP 62%, JW 70% and IMA 70% [p = 0.7]), blinding status of health care providers (ACP 12%, JW 4% and IMA 4% [p = 0.4]) and blinding status of judicial assessors of outcomes (ACP 4%, JW 4% and IMA 0% [p = 0.4]). ACP was the only one to report whether investigators conducted an intention-to-treat analysis (in 38% of summaries [p < 0.001]), and it was more likely than the other 2 journals to report the precision of the treatment effect (as a p value or 95% confidence interval) (ACP 100%, JW 0% and IMA 55% [p < 0.001]). INTERPRETATION: Although ACP provided more information on study design, methodology and results, all 3 secondary journals often omitted important information. More complete reporting is necessary for secondary journals to fulfill their potential to help clinicians evaluate the medical literature.
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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 | 0.678 | 0.928 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.048 | 0.039 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".