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Record W2168925388 · doi:10.1177/0956797610382122

Deconstructing Early Life Experiences

2010· article· en· W2168925388 on OpenAlexafffund
Cynthia de Medeiros, Stephanie Rees, Maheleth Llinas, Alison S. Fleming, David Crews

Bibliographic record

VenuePsychological Science · 2010
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Toronto
FundersNational Institute of Mental HealthNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsLitterPsychologyProceptive phaseDevelopmental psychologySexual behaviorSex ratioLordosisIn uteroHuman sexualityPhysiologyDemographyPregnancyBiologyOvariectomized ratEndocrinologyEcologyEstrogenPopulationFetusMedicine

Abstract

fetched live from OpenAlex

In rodents, a pup's experiences in utero and during postnatal development shape its sexual behavior as an adult and how it is perceived by potential mates. We show that the male rat's sexuality is primarily influenced by the postnatal sex ratio of its litter, but not by the litter's prenatal intrauterine sex ratio or the behavior of its mother. Pups from litters with differing prenatal sex ratios were divided into litters with differing postnatal sex ratios. We found that males raised in a female-biased litter exhibited less mounting than males raised in either a male-biased litter or one with an equal sex ratio, and were less attractive to sexually receptive females, eliciting fewer soliciting behaviors, such as hop-darts, and fewer lordosis behaviors. However, the number of intromissions and ejaculations did not differ across groups, which suggests that males from female-biased litters mate as efficiently as males raised in other sex ratios, but do not require as many mounts to do so. The reported differences in sexual behavior did not vary with the quality of maternal behavior or with sexual experience in adulthood.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.425
Teacher spread0.373 · 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

Citations16
Published2010
Admission routes2
Has abstractyes

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