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Record W2108464813 · doi:10.1186/1471-2288-1-13

Determinants of abstract acceptance for the Digestive Diseases Week – a cross sectional study

2001· article· en· W2108464813 on OpenAlexaff
Antje Timmer, Robert J. Hilsden, L. R. Sutherland

Bibliographic record

VenueBMC Medical Research Methodology · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsUniversity of Calgary
FundersDeutscher Akademischer Austauschdienst
KeywordsCross-sectional studyMedicineSample size determinationFamily medicineClinical trialStatistical significancePresentation (obstetrics)DemographyInternal medicineSurgeryPathologyStatisticsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: The Digestive Diseases Week (DDW) is the major meeting for presentation of research in gastroenterology. The acceptance of an abstract for presentation at this meeting is the most important determinant of subsequent full publication. We wished to examine the determinants of abstract acceptance for this meeting. METHODS: A cross-sectional study was performed, based on abstracts submitted to the DDW. All 17,205 abstracts submitted from 1992 to 1995 were reviewed for acceptance, country of origin and research type (controlled clinical trials (CCT), other clinical research (OCR), basic science (BSS)). A random sub-sample (n = 1,000) was further evaluated for formal abstract quality, statistical significance of study results and sample size. RESULTS: 326 CCT, 455 OCR and 219 BSS abstracts were evaluated in detail. Abstracts from N/W Europe (OR 0.4, 95% CI 0.3-0.6), S/E Europe (OR 0.4, 95% CI 0.2-0.6) and non-Western countries (OR 0.3, 95% CI 0.2-0.5) were less likely to be accepted than North-American contributions when controlling for research type. In addition, the OR for the acceptance for studies with negative results as compared to those with positive results was 0.4 (95% CI 0.3-0.7). A high abstract quality score was also weakly associated with acceptance rates (OR 1.4, 95% CI 1.0-2.0). CONCLUSIONS: North-American contributions and reports with statistically positive results have higher acceptance rates at the AGA. Formal abstract quality was also predictive for acceptance.

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)0.547
metaresearch head score (Gemma)0.843
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5470.843
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.000

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.

Opus teacher head0.965
GPT teacher head0.744
Teacher spread0.221 · 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
Domainnot available
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

Citations24
Published2001
Admission routes1
Has abstractyes

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