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Record W1497317113 · doi:10.1002/0470870818.ch14

Oestrogen and Cognitive Function Throughout the Female Lifespan

2000· review· en· W1497317113 on OpenAlexaff
Barbara B. Sherwin

Bibliographic record

VenueNovartis Foundation symposium · 2000
Typereview
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsCognitionMenstrual cycleCognitive agingPostmenopausal womenAgeingVerbal memoryEstrogenPsychologyDevelopmental psychologyPhysiologyMedicineMenopauseCognitive skillEndocrinologyInternal medicineNeuroscienceHormone

Abstract

fetched live from OpenAlex

Evidence that oestrogen helps to maintain verbal memory in women comes from several sources. Studies that have tested cognitive functioning at different phases of the menstrual cycle have found few differences, perhaps because oestrogen levels are sufficiently high, albeit variable, during all cycle phases. Experimental studies in postmenopausal women have generally found a protective effect of oestrogen, specifically on verbal memory. Results of several large, longitudinal studies that have become available recently have also demonstrated that women who were oestrogen users performed better on certain tests of cognitive function than non-users of similar age. On the basis of this body of evidence, it is possible to conclude that oestrogen may attenuate or prevent the decline in aspects of memory that occur with normal ageing in women.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.087
GPT teacher head0.403
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations53
Published2000
Admission routes1
Has abstractyes

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