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Record W1831738305 · doi:10.1186/1471-2288-2-7

Publication bias in gastroenterological research – a retrospective cohort study based on abstracts submitted to a scientific meeting

2002· article· en· W1831738305 on OpenAlexaff
Antje Timmer, Robert J. Hilsden, John W. Cole, David Hailey, Lloyd R. Sutherland

Bibliographic record

VenueBMC Medical Research Methodology · 2002
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersDeutscher Akademischer Austauschdienst
KeywordsMedicinePublication biasLogistic regressionFamily medicineImpact factorMEDLINECohort studyPublicationInternal medicineMeta-analysis

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to examine the determinants of publication and whether publication bias occurred in gastroenterological research. METHODS: A random sample of abstracts submitted to DDW, the major GI meeting (1992-1995) was evaluated. The publication status was determined by database searches, complemented by a mailed survey to abstract authors. Determinants of publication were examined by Cox proportional hazards model and multiple logistic regression. RESULTS: The sample included abstracts on 326 controlled clinical trials (CCT), 336 other clinical research reports (OCR), and 174 basic science studies (BSS). 392 abstracts (47%) were published as full papers. Acceptance for presentation at the meeting was a strong predictor of subsequent publication for all research types (overall, 54% vs. 34%, OR 2.3, 95% CI 1.7 to 3.1). In the multivariate analysis, multi-center status was found to predict publication (OR 2.8, 95% CI 1.6-4.9). There was no significant association between direction of study results and subsequent publication. Studies were less likely to be published in high impact journals if the results were not statistically significant (OR 0.5, 95 CI 95% 0.3-0.6). The author survey identified lack of time or interest as the main reason for failure to publish. CONCLUSIONS: Abstracts which were selected for presentation at the DDW are more likely to be followed by full publications. The statistical significance of the study results was not found to be a predictor of publication but influences the chances for high impact publication.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.914
metaresearch head score (Gemma)0.962
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.9140.962
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0060.013
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0050.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0400.010

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.

Opus teacher head0.977
GPT teacher head0.706
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
DomainMethods
GenreEmpirical

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".

Quick stats

Citations103
Published2002
Admission routes1
Has abstractyes

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