Comparison of Acceptance ofClinical versus Basic Studies onDrugs and Therapeutics inInfants and Children
Bibliographic record
Abstract
Many clinicians and clinician-scientists have serious concerns that clinical studies (i.e. studies with patients) are less favorably accepted than basic ('bench') projects by funding agencies and by promotion committees of university departments. However, this commonly held view has not been previously verified. To test whether bias exists against clinical studies, we compared the acceptance rate of clinical vs. basic studies dealing with drugs and therapeutics in children, which were submitted to a large scientific meeting. Of 197 abstracts reporting on drug/therapeutic studies, submitted to the Society for Pediatric Research in 1993, there were 133 clinical and 64 basic studies. Fifty-nine (44.3%) of the clinical studies were accepted, significantly less than the basic projects (n = 47 or 73.4%, p < 0.0001). A basic paper was 66% more likely to be accepted (95% CI 50.7-82.6%). This trend was consistent for different groups of drugs/therapeutics, including analgesics, surfactants, corticosteroids, vaccines, hormones, and antiasthmatics. To examine whether the lower rate of acceptance of clinical papers is the result of lower scientific standard, all papers were scored for their quality by raters who were blinded to their acceptance or rejection status. In general, rejected clinical papers scored significantly higher than rejected basic papers (16 +/- 1.8 vs. 14.8 +/- 1.0, p < 0.05). Our study supports the commonly held but previously unproven view that there is a bias against clinical research, in the context of patient-based studies, when compared to basic (bench) research.
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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 | 0.297 | 0.578 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".