MétaCan
Menu
Back to cohort
Record W6964673681 · doi:10.3205/23ebm059

Datenbankkombinationen für die Recherche systematischer Reviews: eine aktualisierte methodische Studie

2023· article· de· W6964673681 on OpenAlexaff

Bibliographic record

VenueGerman Medical Science (German Research Foundation) · 2023
Typearticle
Languagede
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsCochrane
Fundersnot available
KeywordsMEDLINEContext (archaeology)Systematic reviewData collection

Abstract

fetched live from OpenAlex

Hintergrund/Fragestellung: Systematische Reviews (SR) sind eine wesentliche Quelle für evidenzbasierte Informationen zu gesundheitsbezogenen Themen. In einer vorangehenden methodischen Studie kamen wir zu dem Ergebnis, dass für die Recherche nach SRs eine Kombination aus MEDLINE und Epistemonikos [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)0.417
metaresearch head score (Gemma)0.676
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 score0.583
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4170.676
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0070.011
Bibliometrics0.0380.029
Science and technology studies0.0030.004
Scholarly communication0.0170.010
Open science0.0050.011
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0550.013

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 head0.400
GPT teacher head0.507
Teacher spread0.107 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGerman Medical Science (German Research Foundation)Same topicForest Ecology and Biodiversity StudiesFrench-language works237,207