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Record W6931937961 · doi:10.5683/sp3/gcry1u

Search strategies for transnational families and pregnancy, childbirth and postpartum care / Stratégies de recherche sur les familles transnationales, la grossesse, l'accouchement et les soins postnataux

2025· dataset· fr· W6931937961 on OpenAlexaff

Bibliographic record

VenueBorealis · 2025
Typedataset
Languagefr
FieldComputer Science
TopicBayesian Methods and Mixture Models
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsycINFOCINAHLMEDLINEChildbirthHealth carePostpartum period

Abstract

fetched live from OpenAlex

Ce jeu de données contient les stratégies de recherche pour CINAHL Complete (EBSCOhost), MEDLINE All (Ovid), Embase (Ovid), Global Health (Ovid), Social Sciences Abstracts (EBSCOhost), APA PsycInfo (Ovid).Quand on les exécute dans leur base de données respective, ces stratégies repêchent les articles sur, inclusivement, les concepts des familles transnationales, la grossesse, l’accouchement et les soins postnataux. Le nombre de résultat et les stratégies de recherche pour chaque base de données sont indiqués dans le fichier rtf. La date indiquée dans cette description est la date à laquelle la recherche a été effectuée. (29 juillet 2024; 2024-07-29).

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)0.009
metaresearch head score (Gemma)0.060
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 score0.057
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.060
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0240.027
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0040.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0570.021

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 head0.109
GPT teacher head0.369
Teacher spread0.260 · 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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