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Record W4409734398 · doi:10.14814/phy2.70325

Comparison of two ovulation tests to predict timing of the late follicular phase for menstrual cycle research in premenopausal females

2025· article· en· W4409734398 on OpenAlexafffund
Lindsay A. Lew, Kyra E. Pyke

Bibliographic record

VenuePhysiological Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsOvulationFollicular phaseMenstrual cycleLuteinizing hormoneEstrogenInternal medicineEndocrinologyMedicineHormone

Abstract

fetched live from OpenAlex

Menstrual cycle peak estradiol occurs in the late follicular (LF) phase just prior to the luteinizing hormone (LH) surge and ovulation. Therefore, to examine the impact of menstrual cycle estradiol fluctuations, it is desirable to perform assessments closely prior to ovulation. Standard ovulation tests (SOT) identify the LH surge and confirm that ovulation occurred after LF testing. Advanced ovulation tests (AOT) detect a rise in estrogen before the LH surge. We hypothesized that using the AOT to schedule LF testing between the rise in estradiol and LH surge would decrease the LF visit:ovulation interval vs. the SOT. Twenty-one naturally menstruating females (22 ± 4 years) participated in an early follicular (EF) and LF visit. The LF visit scheduling employed an AOT (n = 10) or SOT (n = 11). There was no difference in the LF visit:ovulation interval between tests (AOT = 2.7 ± 2.2 days, SOT = 2.5 ± 1.7 days; p = 0.859). Estradiol increased from the EF to LF phase, regardless of the ovulation test used (phase p < 0.001, test p = 0.528, interaction p = 0.099), and Δestradiol was negatively correlated with LF visit:ovulation interval (r = -0.454, p = 0.050). In this preliminary study, the AOT estrogen signal did not support scheduling the LF visit closer to ovulation or during higher estradiol vs. the SOT. Future studies should explore different methods to identify the menstrual cycle estradiol peak.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.204
GPT teacher head0.495
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

Citations1
Published2025
Admission routes2
Has abstractyes

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