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Record W2986705118 · doi:10.1016/j.ajog.2019.10.096

Rates of recognized pregnancy in women with disabilities in Ontario, Canada

2019· letter· en· W2986705118 on OpenAlexafffundabout
Hilary K. Brown, Simon Chen, Astrid Guttmann, Susan M. Havercamp, Susan L. Parish, Joel G. Ray, Lesley A. Tarasoff, Simone N. Vigod, Adele Carty, Yona Lunsky

Bibliographic record

VenueAmerican Journal of Obstetrics and Gynecology · 2019
Typeletter
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsCentre for Addiction and Mental HealthSt. Michael's HospitalInstitute for Clinical Evaluative SciencesHospital for Sick ChildrenThe Scarborough HospitalPublic Health OntarioWomen's College HospitalUniversity of Toronto
FundersNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentInstitute for Clinical Evaluative Sciences
KeywordsMedicinePregnancyObstetricsFamily medicineGynecologyGerontology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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 designObservational
Domainnot available
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

Citations71
Published2019
Admission routes3
Has abstractno

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