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Record W172004509 · doi:10.1007/0-306-46887-5_5

Is-It Possible to Detect Bovine Treated with BST?

2005· book-chapter· en· W172004509 on OpenAlexaboutno aff
Carolina Pacheco Bertozzi, Daniel Portetelle, M. Pirard, Isabelle Parmentier, Valérie Haezebroeck, Robert Renaville

Bibliographic record

VenueKluwer Academic Publishers eBooks · 2005
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsnot available
Fundersnot available
KeywordsBovine somatotropinLivestockBiotechnologyAgricultureIdentification (biology)Dairy cattleControl (management)BusinessSelection (genetic algorithm)Administration (probate law)Animal healthAnimal agricultureAgricultural scienceBiologyGrowth hormonePolitical scienceEconomicsAnimal scienceComputer scienceLawManagementEndocrinology

Abstract

fetched live from OpenAlex

Biotechnology has been heralded as a science that will have a revolutionary impact on agriculture development. Joint efforts among industry, universities, and authorities will result in new and novel products that establish new frontiers in the livestock industries. One of the first biotechnology products is somatotropin. The galactopoietic effect of bovine somatotropin in dairy cows has been firmly established. Also, administration of exogenous somatotropin markedly improves productive efficiency in lactating cows. However, in the international network, a control strategy of treated animals is required not only because BST use is not authorised in Europe and in Canada, but also because rbST treatment interferes with the genetic selection scheme of reproductive animals. Besides studies on eventual adverse effects on animal health, ethical aspects as well as consumer protection have to be considered. Therefore, the present review tends to describe different possible ways to develop strategies for identification of BST treated cattle.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.228
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.247
Teacher spread0.212 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueKluwer Academic Publishers eBooksSame topicReproductive Physiology in LivestockFrench-language works237,207