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Record W1964069126 · doi:10.1586/14737175.4.5.851

Role of progesterone and other neuroactive steroids in anxiety disorders

2004· review· en· W1964069126 on OpenAlexaff
Jean‐Michel Le Mellédo, Glen B. Baker

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2004
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNeuroactive steroidAllopregnanoloneAnxiolyticAnxietyHormoneMenstrual cyclePsychologyMedicinePsychiatryEndocrinologyPharmacologyInternal medicineGABAA receptorReceptor

Abstract

fetched live from OpenAlex

It remains unexplained why a greater prevalence of anxiety disorders exists in women than in men, and how female hormone-related events (i.e., menstrual cycle and postpartum) can influence the course of anxiety disorders. It would appear logical that female hormones and their derivatives play a major role in these observations. The abundance of preclinical data demonstrating a role for sex hormones and their derivatives in anxiety-like behavior is in contrast to the relative paucity of experimental clinical data on the role of female hormones and neuroactive steroids in anxiety disorders. There is a dramatic potential for therapeutic anxiolytic activity of pharmacological compounds derived from powerful anxiolytic agents, such as the progesterone derivative, allopregnanolone. As a result, there is currently tremendous interest from the pharmaceutical industry in developing and testing such agents in anxiety disorders.

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 score0.004
Threshold uncertainty score0.012

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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.368
Teacher spread0.317 · 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

Citations44
Published2004
Admission routes1
Has abstractyes

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