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Record W1585740257 · doi:10.1159/000106490

Age-Related Changes in Antral Follicle Count among Women with and without Polycystic Ovaries

2007· article· en· W1585740257 on OpenAlexaffabout
Mohammed Al-Sunaidi, Sharifa Al-Mahrizi, Seang Lin Tan, Togas Tulandi

Bibliographic record

VenueGynecologic and Obstetric Investigation · 2007
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsAntral folliclePolycystic ovaryFollicular phaseFollicle-stimulating hormoneFollicleBasal (medicine)Ovarian follicleOvaryMedicineInternal medicineEndocrinologyGonadotropinMenstrual cycleOvarian reserveHormoneBiologyGynecologyAndrologyLuteinizing hormoneInfertilityPregnancy

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: To evaluate follicular phase antral follicle count (AFC) in women of different ages with and without polycystic ovaries (PCO) and to correlate it with early follicular phase serum follicle stimulating hormone (FSH), estradiol, and ovarian volume. METHODS: Retrospective analysis of 1,003 patients' medical records at McGill Reproductive Center. AFC, ovarian volume, serum FSH and estradiol were evaluated and analyzed. RESULTS: The mean numbers of AFC in women without PCO in the age-groups 19-24, 25-29, 30-34, 35-39, 40-44 years were 16, 13, 13, 10, and 6, and in those with MCO 41, 38, 33, 33 and 34 respectively. In women without MCO, AFC was associated with the strongest correlation with age (r: -0.50, p < 0.0001), followed by basal FSH (r: 0.33, p <0.0001). The correlations in women with PCO were less pronounced (AFC, r: -0.24, p < 0.0001; basal FSH, r: 0.17, p < 0.004). CONCLUSIONS: Compared to women without PCO, age-related decreases in AFC and changes in ovarian volume and FSH levels in women with PCO are less pronounced.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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

Citations12
Published2007
Admission routes2
Has abstractyes

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