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Record W4410449768 · doi:10.1111/age.70017

Animal genetics 100 years ago

2025· article· en· W4410449768 on OpenAlexaboutno aff
F. W. Nicholas

Bibliographic record

VenueAnimal Genetics · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
Fundersnot available
KeywordsMendelian inheritanceBiologyInbreedingGeneticsGeneticistGenealogyPedigree chartHeterosisQuantitative geneticsAnimal breedingDemographyPopulationGenetic variationSociologyHistoryHybridGene

Abstract

fetched live from OpenAlex

One hundred years ago, the first book with the phrase "Animal Genetics" in its title was published. It was written by F.A.E. Crew, then Lecturer in Genetics and foundation Director of the Department of Research in Animal Breeding at the University of Edinburgh. The 352 pages of text provide a most interesting summary of the knowledge of animal genetics at that time. It is impressive to see the extent to which the understanding of genetics had developed in just a couple of decades since the rediscovery of Mendelism. There was, for example, recognition that genes are borne on chromosomes; that XX/XY sex determination provides a very satisfactory explanation for most of the relevant evidence; that sex-linked inheritance has a practical application; that variation in quantitative traits is determined by the combined action of many genes and many non-genetic factors; that inbreeding results in substantial decreases in fecundity and fertility due to homozygosity for undesirable alleles; that crossing between lines or breeds gives rise to hybrid vigour (heterosis); and that many disorders are inherited in a Mendelian fashion, and hence can be controlled by informed breeding. There is, however, no mention of Fisher's 1918 paper nor of Wright's recently published inbreeding coefficient and coefficient of relationship. Crew's book inspired the next generation of geneticists, such as Fred Hutt, who travelled from Canada to Edinburgh to do a PhD with Crew, and who later published his own very influential book with the same title, which was dedicated to Crew.

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)0.002
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0220.028

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 head0.264
Teacher spread0.253 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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