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Record W2075143588 · doi:10.1136/emj.2010.101667

Full text publication rates of studies presented at an international emergency medicine scientific meeting

2010· article· en· W2075143588 on OpenAlexaboutno aff
Johnny Wai Man Chan, Colin A. Graham

Bibliographic record

VenueEmergency Medicine Journal · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePresentation (obstetrics)Medical emergencyEmergency medicineLibrary scienceRadiology

Abstract

fetched live from OpenAlex

The publication rate of full text papers following an abstract presentation at a medical conference is variable, and few studies have examined the situation with respect to international emergency medicine conferences. This retrospective study aimed to identify the publication rate of abstracts presented at the 2006 International Conference on Emergency Medicine (ICEM) held in Halifax, Canada. The full text publication rate was 33.2%, similar to previous emergency medicine meetings. English language barriers may play a role in the low publication rate seen.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.177
metaresearch head score (Gemma)0.582
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1770.582
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.010
Bibliometrics0.0270.030
Science and technology studies0.0010.001
Scholarly communication0.0070.006
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.723
GPT teacher head0.594
Teacher spread0.129 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainReporting
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

Citations34
Published2010
Admission routes1
Has abstractyes

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