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Record W3013780456 · doi:10.1186/s12978-020-0858-7

Authorship in studies conducted in low-and-middle income countries and published by Reproductive Health: advancing equitable global health research collaborations

2020· editorial· en· W3013780456 on OpenAlexaff
Verónica Pingray, Vanesa Ortega, Sanni Yaya, José M. Belizán

Bibliographic record

VenueReproductive Health · 2020
Typeeditorial
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReproductive medicinePublic healthLow and middle income countriesReproductive healthGlobal healthEnvironmental healthDeveloping countryPolitical scienceEconomic growthSocioeconomicsMedicineBiologyPopulationSociologyPregnancyEconomics

Abstract

fetched live from OpenAlex

Reproductive Health has an interest in reproductivehealth status globally, but it has particular interest inphenomena affecting disadvantaged populations. This isthe reason why this journal encourages submissionsfrom researchers conducting studies in low- and middleincome countries (LMICs).

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)0.038
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.977
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.123
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0060.003
Science and technology studies0.0050.004
Scholarly communication0.0160.010
Open science0.0050.003
Research integrity0.0230.020
Insufficient payload (model declined to judge)0.0260.013

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 head0.093
GPT teacher head0.446
Teacher spread0.354 · 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 designNot applicable
DomainIncentives
GenreEditorial

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

Citations19
Published2020
Admission routes1
Has abstractyes

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