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Record W2536674167 · doi:10.1038/ajg.2016.446

How to Interpret a Negative Study

2016· article· en· W2536674167 on OpenAlexaffabout
Grigorios I. Leontiadis

Bibliographic record

VenueThe American Journal of Gastroenterology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsHealth Sciences CentreMcMaster University
Fundersnot available
KeywordsMedicineFamily medicineLibrary science

Abstract

fetched live from OpenAlex

1Department of Medicine, Division of Gastroenterology, Farncombe Family Digestive Health Research Institute, McMaster University Health Sciences Centre, Hamilton, Ontario, Canada Correspondence: Grigorios I Leontiadis, MD, PhD, Department of Medicine, Division of Gastroenterology, Farncombe Family Digestive Health Research Institute, McMaster University Health Sciences Centre, 1280 Main St. West, Suite 3V3, Hamilton, Ontario L8S 4K1, Canada. E-mail: [email protected] Guarantor of the article: Grigorios I. Leontiadis, MD, PhD. Specific author contributions: Grigorios I. Leontiadis is the sole contributor and has approved the final draft submitted. Financial support: None. Potential competing interests: None.

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)0.294
metaresearch head score (Gemma)0.715
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.706
Threshold uncertainty score0.871

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2940.715
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0090.003
Science and technology studies0.0070.018
Scholarly communication0.0180.019
Open science0.0070.006
Research integrity0.0150.019
Insufficient payload (model declined to judge)0.0190.009

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 head0.063
GPT teacher head0.450
Teacher spread0.387 · 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 designNot applicable
DomainMethods
GenreMethods

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

Citations4
Published2016
Admission routes2
Has abstractyes

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