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Factors Associated with Publication Following Presentation at a Transplantation Meeting

2006· article· en· W2058976652 on OpenAlexaff
Naomi Glick, Iain Macdonald, Greg Knoll, Alain Brabant, Sita Gourishankar

Bibliographic record

VenueAmerican Journal of Transplantation · 2006
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversity of OttawaUniversity of Alberta
Fundersnot available
KeywordsMedicineTransplantationPresentation (obstetrics)Clinical trialMeta-analysisMultivariate analysisRandomized controlled trialPublication biasFamily medicineInternal medicineSurgery

Abstract

fetched live from OpenAlex

Full publication of abstracts presented at scientific meetings ranges from 25-74%. To determine the rate and factors associated with publication in organ transplantation, we examined abstracts presented at the American Transplant Congress in May 2000. Of 1147 abstracts, 607 (53%) achieved full publication at 4.5 years (mean 1.32 +/- 0.88 years). Fifty-nine percent (357/607) were published in three transplantation journals. For randomized trials, the proportion published was 61%. On multivariate analysis, industry sponsorship (OR 1.78; 95% CI 1.04-3.06), basic science research (OR 1.68; 95% CI 1.32-2.14), non-American center (OR 1.67; 95% CI 1.28-2.20) and oral presentation (OR 1.36; 95% CI 1.07-1.73) were independent predictors of full publication. Nearly half of all abstracts presented at a transplantation meeting remain unpublished. This finding needs to be considered when interpreting systematic reviews in the field of transplantation.

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)0.069
metaresearch head score (Gemma)0.337
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.337
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0120.016
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.004

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 head0.251
GPT teacher head0.479
Teacher spread0.227 · 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
DomainEvaluation
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

Citations26
Published2006
Admission routes1
Has abstractyes

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