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Record W4411049428 · doi:10.1016/j.xagr.2025.100525

A descriptive analysis of a fertility services waitlist in Eastern Canada

2025· article· en· W4411049428 on OpenAlexafffundabout
Hannah M. Murphy, Heather Manning, Zohreh Zeidy, Sarah Benson, John Cullen, Deanna Murphy, Séan Murphy, Sarah Healey, Laurie Twells, Katie P. Wadden

Bibliographic record

VenueAJOG Global Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsMemorial University of Newfoundland
FundersMedicinska fakulteten, Umeå UniversitetFaculty of Medicine, Memorial University of Newfoundland
KeywordsFertilityDescriptive statisticsGeographyDemographySociologyStatisticsMathematicsPopulation

Abstract

fetched live from OpenAlex

ABSTRACT Objective Infertility is common and impacts quality of life. Maternal age is an important factor in fertility status, and therefore, timely access to care is critical. Long waits for specialist care remain a reality in Canada, representing an opportunity for early intervention. This study aimed to characterize the population seeking infertility care in Newfoundland and Labrador (NL). Methods A province-wide, cross-sectional analysis of referrals to Newfoundland and Labrador Fertility Services (NLFS) was conducted. De-identified data were extracted from patient records. Descriptive analyses of the reason for referral, provincial geographical health zone, and female age, and a comparison of the age of patients referred across the province were completed. Historical live birth data were used to adjust for population differences. Results There were 317 eligible referrals received by NLFS over a six-month period. The most common reason for referral was infertility (n=221, 70%). The overall mean age of referred females was 33.09 years ( SD =5.03). The Eastern-Urban region had the highest number of referrals (n=145, 66%), which was greater than expected based on live birth rates ( p ≤.001). Patients referred from areas outside of the Eastern-Urban region were younger ( p ≤.001). Conclusion Infertility was the most common reason for referral. The age of females referred for infertility emphasizes the need for prompt intervention. There were differences in referral patterns across the province, including a disproportionately high referral rate in the Eastern-Urban region.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.303
Teacher spread0.290 · 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 teacher head, 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 routes3
Has abstractyes

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