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Record W4311692627 · doi:10.1053/j.ajkd.2022.10.015

Sex and Gender in Randomized Controlled Trials of Adults Receiving Maintenance Dialysis: A Meta-epidemiologic Study

2022· article· en· W4311692627 on OpenAlexaff
David Collister, Lonnie Pyne, Arrti Bhasin, Sofia B. Ahmed, Brendan Smyth, William G. Herrington, Meg Jardine, Michael Walsh

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2022
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsImpactMcMaster UniversityPopulation Health Research InstituteUniversity of CalgaryUniversity of Alberta
FundersMedical Research Council
KeywordsMedicineRandomized controlled trialMeta-analysisDialysisMEDLINEGerontologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchMeta-epidemiology (broad)
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptMetaresearchMeta-epidemiology (broad)
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Meta-analysismedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.017
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.042
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0130.035
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0040.003
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 head0.089
GPT teacher head0.376
Teacher spread0.287 · 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

Labeled directly by 2 models reading the full record.

MetaresearchMeta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Meta-analysis
DomainMethods · Reporting
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

Citations14
Published2022
Admission routes1
Has abstractno

Explore more

Same venueAmerican Journal of Kidney DiseasesSame topicSex and Gender in HealthcareCategoryMetaresearchFrench-language works237,207