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Record W4409158050 · doi:10.1080/23293691.2025.2482608

Pregnancy Outcomes and Perspectives in Women With Spinal Cord Injuries Undergoing Fertility Treatment: A Cross-Sectional Survey Study

2025· article· en· W4409158050 on OpenAlexafffund
Trish Dinh, Claire Mazzia, Anne Berndl

Bibliographic record

VenueWomen s Reproductive Health · 2025
Typearticle
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsUniversity of Toronto
FundersOntario Neurotrauma Foundation
KeywordsCross-sectional studyFertilityMedicinePregnancyObstetricsGynecologyEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

Women with spinal cord injuries (SCI) who conceived spontaneously or with fertility treatment from the Spinal Cord Injury, Urogenital Health and Pregnancy (SCI-UP) survey were compared. We included 350 pregnancies from 193 participants with at least one pregnancy following SCI. Fertility treatment occurred in 5.1% of pregnancies. Live birth rate was 66.7% with treatment vs. 64.5% without (odds ratio, 1.97; 95% confidence interval, 0.40–9.69; p = .41). Time to first conception was longer in the treatment group (median, 12 [interquartile range, 9–14) vs. 6 years 3–12]). No differences were seen in major obstetrical complications between groups.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.440
Teacher spread0.346 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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