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History of Scientific Agriculture: Animals

2016· other· en· W1530914456 on OpenAlexaff
Robert P. Thompson

Bibliographic record

VenueEncyclopedia of Life Sciences · 2016
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDomesticationTraitAgricultureBiologyBiotechnologySelection (genetic algorithm)Animal agricultureEvolutionary biologyEcologyComputer science

Abstract

fetched live from OpenAlex

Abstract Domestication of agricultural animals began 10 000 years ago. From a wide array of wild animals, only a small number were and, for specifiable reasons, could be domesticated. Trait selection and breeding has been the principal mechanism of animal improvement until the late twentieth century. As with much of early science, enhancing beneficial traits was a trial and error process. An understanding of the genetic mechanisms and environmental factors in that process was a twentieth‐century triumph. Drawing on physiological, behavioural, genetic, evolutionary and ecological knowledge significantly enhanced selection and breeding efforts. In the twentieth century, scientific advancements were numerous. Of special significance were the introduction of artificial insemination, and the nature, prevention and treatment of pathogenic diseases. Late twentieth‐century agricultural biology began to employ techniques of molecular genetic manipulation (transgenic animals), initially using farm animals as bioreactors. Improvements in cloning, pronuclear injection and use of stem cells can be expected to dominate research and development in twenty‐first‐century animal agriculture. Key Concepts The early evolution of animal domestication was trial and error. Human and agricultural animals coevolved. The mechanisms of speciation were important processes in the early period but only well understood in the twentieth century. The quantitative genetics of farm animal makes trait improvement challenging. Critical variables in the trait farm animals are understood but difficult to manipulate. The importance of multiple trait selection is now well understood. Artificial insemination and cryopreservation of sperm have significantly improved trait manipulation and preservation. Knowledge of pathogens has allowed antibiotics and sanitation to be effectively employed. Animals as pharmaceutical and material bioreactors has been recent and expanded the genetic modification of animals. There are challenges and promises of cloning, pronuclear injection and stem cell use in animal agriculture emerging in the twenty‐first century.

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)0.004
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 score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.011
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0300.018

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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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
Published2016
Admission routes1
Has abstractyes

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