Association between statistical significance and time to publication among systematic reviews: a study protocol for a meta-epidemiological investigation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Many studies have indicated the impact of bias in dissemination and publication in medical research. Existence of such bias among clinical trials has been repeatedly pointed out, but it has not been well studied in the field of systematic reviews (SRs). We therefore aim to investigate whether or not time lag bias and publication bias in SRs based on statistical significance in results exist. In addition, we will examine at what stage of paper publication process such bias, if any, creeps in. METHOD AND ANALYSIS: The present study is a meta-epidemiological study. We will include all SRs of interventions registered in the international prospective register of SRs (PROSPERO) before December 2014 if the SR has completed its analysis irrespective of its publication status. All contact authors of eligible SRs will be asked to participate in a survey administered through the Internet. Our primary outcome is time from protocol registration to full publication of SR as a journal article, defined as time from the registration date to the acceptance date among all the relevant SRs. We will examine the impact of statistically significant findings on the primary outcomes through time to event analyses. ETHICS AND DISSEMINATION: Ethics approval will be obtained from the Ethical Committee of the Kyoto University Graduate School of Medicine. This protocol has been registered in the University Hospital Medical Information Network Clinical Trials Registry. We will publish our findings in a peer-reviewed journal and also may present them at conferences. TRIAL REGISTRATION NUMBER: UMIN000028325.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad)Meta-epidemiology (narrow) Domain: Evaluation · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Meta-epidemiology (narrow)Meta-epidemiology (broad)Metaresearch Domain: Evaluation · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.437 | 0.622 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it