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Record W2187726817

Genes in genital malformations and male reproductive health

2004· article· en· W2187726817 on OpenAlexaff
Parvathi K. Basrur, V. Basrur

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyConceptusGeneticsGeneSexual differentiationInbreedingSex organPregnancyPopulationFetusMedicine
DOInot available

Abstract

fetched live from OpenAlex

Genital malformations constitute the most common birth defects encountered in man and domestic animals. They occur more frequently in genetic males since the participation of many genes is required for sex differentiation to proceed in the male direction. The emerging insight, through the identification of genes involved in the sex differentiation cascade, is that over 85 percent of sex anomalies in human and domestic animal populations are not attributable to chromosome aberrations or to mutations in a known gene. Since a majority of severely malformed individuals are incapable of reproduction, the high rates of these defects have to be the results either of new mutations or of collaboration of environmental factors with genes. Increase in the prevalence of specific malformations in domestic animals often indicates increased concentration of liability genes brought together in the conceptus by inbreeding. However, in human populations where inbreeding is not the norm, such increases may reflect environment-induced new mutations or interaction of environmental agents with hormone sensitive genes. This review summarizes the information currently available on the genetics of major events in male sex differentiation and briefly discusses the collaborative role environment may play in disrupting different components of this process.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.000

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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
Published2004
Admission routes1
Has abstractyes

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