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Record W2204799712 · doi:10.3758/bf03330634

Intense arousal of novel male mice in proximity to previously inseminated females: Inactivation of males via chlorpromazine does not diminish the capacity to disrupt pregnancy

2000· article· en· W2204799712 on OpenAlexaff
Denys deCatanzaro, Cameron Muir, Emily Spironello, Tamara Binger, Jeff Thomas

Bibliographic record

VenuePsychobiology · 2000
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPregnancyChlorpromazineArousalSedationPsychologyPhysiologyEndocrinologyInternal medicineDevelopmental psychologyMedicineBiologyAnesthesiaNeuroscienceGenetics

Abstract

fetched live from OpenAlex

In the course of investigating early pregnancy disruptions by novel males, intense behavioral interactions and chemical emissions were observed among males housed in proximity to inseminated females. These interactions were evident despite wire-mesh separations between males and females. Experiments were designed to examine whether such arousal plays a role in pregnancy disruption. During the first 5 days of pregnancy, inseminated CF-1 strain female mice were either left undisturbed or exposed to novel outbred males. Physical separations between males did not diminish the frequency of pregnancy disruption. Subsequently, we investigated whether heavy sedation of novel males via chronic chlorpromazine administration would diminish the capacity to disrupt pregnancy. Pregnancy was disrupted to the same degree in females exposed to drug-treated males and those exposed to alert competing males given vehicle injections. These data show an unprecedented degree of arousal and pheromonal emission among competing males but suggest that these factors are not critical for the capacity to disrupt pregnancy.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.127
GPT teacher head0.302
Teacher spread0.175 · 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

Citations8
Published2000
Admission routes1
Has abstractyes

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