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Record W7093294563 · doi:10.5683/sp3/mkrk8l

Search strategies for Severe asthma remission in adults / Stratégies de recherche sur la Rémission de l'asthme sévère chez l'adulte

2025· dataset· W7093294563 on OpenAlexaff

Bibliographic record

VenueBorealis · 2025
Typedataset
Language
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMEDLINECochrane LibraryAsthmaVocabularyDisease

Abstract

fetched live from OpenAlex

This dataset contains the full MEDLINE (using the MEDALL segment, 1946-) and Embase (from 1974-) search strategies. These databases were searched without language restriction, all via Ovid. The search strategy used text words and database-appropriate controlled vocabulary (indexing) to retrieve publications on moderate to severe asthma remission in adults. We retrieved results published later than 2014, when another search had been done. Ce jeu de données contient les stratégies de recherche complètes pour MEDALL (1946-) et Embase (1974-), toutes via Ovid. Nous avons cherché par mots-clés et par vocabulaire contrôllé propre à chaque base de données les concepts rémission, asthme modéré à sévère, et adulte. Nous n'avons pas mis une limite de langue, mais nous avons limité les résultats aux articles publiés après 2014, moment où une autre recherche a été faite.

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)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.031
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0180.018
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0310.014

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 head0.050
GPT teacher head0.367
Teacher spread0.317 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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