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AN OBSERVATIONAL STUDY OF ORTHOPAEDIC ABSTRACTS AND SUBSEQUENT FULL-TEXT PUBLICATIONS

2002· article· en· W2098881266 on OpenAlexaff
Mohit Bhandari, P.J. Devereaux, Gordon Guyatt, M.F. Swiontkowski, Sheila Sprague, Emil H. Schemitsch

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2002
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster University
Fundersnot available
KeywordsObservational studyPresentation (obstetrics)Consistency (knowledge bases)MEDLINEMedicineInformation retrievalLibrary scienceFamily medicineMedical physicsComputer scienceSurgeryPathologyArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Research abstracts are frequently referenced in orthopaedic textbooks and influence orthopaedic care. However, little is known about the quality of information provided in the abstracts, the frequency of publication of complete papers after presentation of abstracts, or any discrepancies between abstracts and published papers. The objective of this study was to determine the quality of information provided in orthopaedic abstracts, rates of publication of full-text articles after presentation of abstracts, predictors of publication of full-text articles, and consistency between abstracts and full-text articles. METHODS: We retrieved all abstracts from the 1996 scientific program of the sixty-third Annual Meeting of the American Academy of Orthopaedic Surgeons. For each abstract, we recorded the completeness of reporting and key features of the study design, conduct, analysis, and interpretation. A computerized Medline and PubMed search established whether the abstract had been followed by publication of a full-text article. Finally, we evaluated the consistency of reporting between abstracts and final publications. RESULTS: The program included 465 abstracts, 66% of which were on prognostic studies. All abstracts described the study design, and 70.7% of the designs were observational. Key methodological issues were reported in less than half of the abstracts, and information on data analysis was reported in <15%. One hundred and fifty-nine (34%) of the 465 abstracts were followed by publication of a full-text article. The mean time to publication (and standard deviation) was 17.6 +/- 12 months (range, one to fifty-six months). Inconsistencies between the abstract and the full-text article included the primary outcome measure, which differed 14% of the time, and the results, which differed 19% of the time. CONCLUSIONS: Two-thirds of the orthopaedic abstracts in this sample were not followed by publication of a full-text paper. The overall quality of reporting in abstracts proved inadequate, and inconsistencies between the final published paper and the original abstract occurred frequently. The routine use of abstracts as a guide to orthopaedic practice needs to be reconsidered.

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)0.070
metaresearch head score (Gemma)0.013
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 score0.087
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0700.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.820
GPT teacher head0.474
Teacher spread0.346 · 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

Citations259
Published2002
Admission routes1
Has abstractyes

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