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Record W2736418032 · doi:10.1002/cbic.201700336

Back Cover: Sex Hormones Function as Sex Attractant Pheromones in House Mice and Brown Rats (ChemBioChem 14/2017)

2017· paratext· en· W2736418032 on OpenAlexaff
Stephen Takács, Regine Gries, Gerhard Gries

Bibliographic record

VenueChemBioChem · 2017
Typeparatext
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiotin and Related Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSex pheromoneTestosterone (patch)PheromoneAttractionHouse miceSexual attractionBiologyHormoneFunction (biology)Cover (algebra)EndocrinologyZoologyInternal medicineSexual behaviorEcologyPsychologyCell biologyDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

The back cover picture shows a female house mouse sensing sex attractant pheromone components [optical isomers of 3,4-dehydro-exo-brevicomin (DEB), (S)-2-(sec-butyl)-4,5-dihydrothiazole (DHT), testosterone] emanating from the urine marking of a male house mouse. Testosterone was well known to control the expression of sexual characteristics and bodily functions of mammals. Here we show that it also elicits attraction behavior in female mice. When we added synthetic testosterone to trap boxes that had already been baited with synthetic DEB and DHT; it increased the capture of adult female mice 15-fold. We predict that testosterone will function as a sex attractant pheromone in diverse taxa. Photo: S.T. More information can be found in the communication by G. Gries et al. on page 1391 in Issue 14, 2017 (DOI: 10.1002/cbic.201700224).

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: Other · Consensus signal: Other
Teacher disagreement score0.169
Threshold uncertainty score0.567

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1690.059

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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