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Record W2085161301 · doi:10.1016/j.ijgo.2010.04.004

The FIGO initiative for the prevention of unsafe abortion

2010· article· en· W2085161301 on OpenAlexaff
Dorothy Shaw

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2010
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsMedicineAbortionUnsafe abortionObstetricsGynecologyEnvironmental healthPregnancyFamily planningPopulationResearch methodology

Abstract

fetched live from OpenAlex

Unsafe abortion is a recognized public health problem that contributes significantly to maternal mortality. At least 13% of maternal mortality is caused by unsafe abortion, mostly in poor and marginalized women. The International Federation of Gynecology and Obstetrics (FIGO) launched an initiative in 2007 to prevent unsafe abortion and its consequences, building on its work on other major causes of maternal mortality. A Working Group was identified with collaborators from many international organizations and terms of reference provided direction from the FIGO Executive Board as to possible evidence-based interventions. A total of 54 member associations of FIGO, representing almost half its member societies, requested participation in the initiative, with 43 subsequently producing action plans that are country specific and involve the national government and multiple collaborators. Obstetrician/gynecologists have demonstrated the importance of the initiative by an unprecedented level of engagement in efforts to reduce maternal mortality and morbidity in country and by sharing experiences regionally.

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)0.008
metaresearch head score (Gemma)0.010
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: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0310.006

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 head0.030
GPT teacher head0.359
Teacher spread0.329 · 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
GenreOther

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

Citations27
Published2010
Admission routes1
Has abstractyes

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