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Record W7065567141

Dopamine-Dependent Task Performance over the Menstrual Cycle

2017· article· en· W7065567141 on OpenAlexaff

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsWestern University
Fundersnot available
KeywordsMenstrual cycleAffect (linguistics)Task (project management)CognitionMenstruationFunction (biology)Fertility
DOInot available

Abstract

fetched live from OpenAlex

Estradiol (E2) has been found to influence dopamine (DA) activity in the nonhuman animal brain. While there has been very little research performed looking at E2’s effects on DA-related cognitive function in humans, recent research found that women tested during high E2 phases of the menstrual cycle had significantly better performance on a DA-dependent spatial working memory task, than women tested during the lowest E2 phase. The current study utilized the natural hormone fluctuations that occur over the menstrual cycle to determine if E2 is associated with DA-dependent task performance. Using a repeated measures design, 47 women completed a battery of tasks, including 3 that are known to depend heavily on DA. The results showed that DA-dependent task performance was significantly associated with menstrual cycle phase. These findings provide preliminary evidence that variations in E2 over the menstrual cycle can affect central DA function in humans.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.051
GPT teacher head0.274
Teacher spread0.222 · 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
Published2017
Admission routes1
Has abstractyes

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