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Record W2733165913 · doi:10.1186/s13104-017-2574-0

Publication bias in animal research presented at the 2008 Society of Critical Care Medicine Conference

2017· article· en· W2733165913 on OpenAlexafffund
Una Conradi, Ari R. Joffe

Bibliographic record

VenueBMC Research Notes · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsStollery Children's HospitalAlberta Health ServicesUniversity of Alberta
FundersUniversity of Alberta
KeywordsRandomizationSample size determinationRandomized controlled trialMedicineResearch designMEDLINEProtocol (science)Test (biology)Family medicinePublication biasStatisticsAlternative medicineInternal medicineMeta-analysisMathematicsPathology

Abstract

fetched live from OpenAlex

BACKGROUND: To determine a direct measure of publication bias by determining subsequent full-paper publication (P) of studies reported in animal research abstracts presented at an international conference (A). METHODS: We selected 100 random (using a random-number generator) A from the 2008 Society of Critical Care Medicine Conference. Using a data collection form and study manual, we recorded methodology and result variables from A. We searched PubMed and EMBASE to June 2015, and DOAJ and Google Scholar to May 2017 to screen for subsequent P. Methodology and result variables were recorded from P to determine changes in reporting from A. Predictors of P were examined using Fisher's Exact Test. RESULTS: 62% (95% CI 52-71%) of studies described in A were subsequently P after a median 19 [IQR 9-33.3] months from conference presentation. Reporting of studies in A was of low quality: randomized 27% (the method of randomization and allocation concealment not described), blinded 0%, sample-size calculation stated 0%, specifying the primary outcome 26%, numbers given with denominators 6%, and stating number of animals used 47%. Only being an orally presented (vs. poster presented) A (14/16 vs. 48/84, p = 0.025) predicted P. Reporting of studies in P was of poor quality: randomized 39% (the method of randomization and allocation concealment not described), likely blinded 6%, primary outcome specified 5%, sample size calculation stated 0%, numbers given with denominators 34%, and number of animals used stated 56%. Changes in reporting from A to P occurred: from non-randomized to randomized 19%, from non-blinded to blinded 6%, from negative to positive outcomes 8%, from having to not having a stated primary outcome 16%, and from non-statistically to statistically significant findings 37%. Post-hoc, using publication data, P was predicted by having positive outcomes (published 62/62, unpublished 33/38; p = 0.003), or statistically significant results (published 58/62, unpublished 20/38; p < 0.001). CONCLUSIONS: Only 62% (95% CI 52-71%) of animal research A are subsequently P; this was predicted by oral presentation of the A, finally having positive outcomes, and finally having statistically significant results. Publication bias is prevalent in critical care animal research.

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)0.547
metaresearch head score (Gemma)0.734
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.453
Threshold uncertainty score0.559

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5470.734
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0180.021
Science and technology studies0.0020.005
Scholarly communication0.0100.006
Open science0.0040.004
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.982
GPT teacher head0.732
Teacher spread0.249 · 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; the direct Gemma label and the distilled Codex classifier 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

Citations11
Published2017
Admission routes2
Has abstractyes

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