MétaCan
Menu
Back to cohort
Record W6908841865 · doi:10.3205/23ebm053

Berücksichtigung von Adhärenz in Cochrane Reviews im Bereich Ernährung: eine Meta-Studie

2023· article· de· W6908841865 on OpenAlexaff

Bibliographic record

VenueGerman Medical Science (German Research Foundation) · 2023
Typearticle
Languagede
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsCochrane
Fundersnot available
KeywordsCochrane collaborationWork (physics)Systematic reviewMEDLINE

Abstract

fetched live from OpenAlex

Hintergrund/Fragestellung: Mangelnde Adhärenz der Teilnehmenden in Ernährungsstudien kann zu einer Verzerrung tatsächlicher Interventionseffekte beitragen [ref:1]. Im 2011 publizierten Cochrane Risk-of-Bias(RoB)-Tool [ref:2] ist die Adhärenz nicht als spezifische [zum vollständigen Text gelangen Sie über die oben angegebene URL]

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)0.172
metaresearch head score (Gemma)0.369
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.828
Threshold uncertainty score0.909

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1720.369
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0210.054
Bibliometrics0.0130.009
Science and technology studies0.0010.002
Scholarly communication0.0090.007
Open science0.0030.005
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.209
GPT teacher head0.509
Teacher spread0.300 · 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 designMeta-analysis
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGerman Medical Science (German Research Foundation)Same topicNutritional Studies and DietFrench-language works237,207