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Record W1964706479 · doi:10.2527/af.2012-0049

Achieving pain control for routine management procedures in North American beef cattle

2012· article· en· W1964706479 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Frontiers · 2012
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversity of CalgaryAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAnimal welfareControl (management)BusinessPain managementInvestment (military)Pain controlBeef cattleWelfareOrder (exchange)MedicineMarketingRisk analysis (engineering)Computer sciencePhysical therapyEconomicsAnesthesiaFinanceBiologyPolitical science

Abstract

fetched live from OpenAlex

Pain control in food animals is an important welfare concern needing attention by the industry, veterinarians, and animal scientists alike. More science-based information is required to develop the best pain control strategies possible. This will include the continued search for the best drug or combination of drugs, administered at the correct time and route relative to the procedure being done and the age of the animal. This also requires the development of appropriate behavioral and physiological pain assessment tools including the appropriate technologies to measure them objectively. In order for pain control strategies to be actively adopted by the industry they must be readily available and registered for use, effective against pain, easy to administer, long acting, have short withdrawal periods, show return on investment, and address public concerns about animal welfare.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.025
GPT teacher head0.301
Teacher spread0.276 · 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