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Record W2130923658 · doi:10.1017/s1466252309990132

Challenges and opportunities for managing respiratory disease in dairy calves

2009· review· en· W2130923658 on OpenAlex
Amy Stanton

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnimal Health Research Reviews · 2009
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBovine respiratory diseaseDiseaseDisease controlWelfareDisease managementIntensive care medicineMedicineBusinessRisk analysis (engineering)Animal welfareControl (management)Economic costEnvironmental healthComputer scienceEconomicsBiologyPathologyImmunology

Abstract

fetched live from OpenAlex

Bovine respiratory disease (BRD) is important for the Ontario dairy industry due to the large economic and welfare costs of this disease. Practical science-based management techniques are needed to control and reduce the risk of this disease. Currently, the emphasis on BRD is focused on early detection of disease and prevention. These areas are important but it is not practical to assume this disease will be eliminated in the near future. It is necessary to determine the best practices for caring for sick animals, monitoring their recovery and making changes to their management to facilitate health and recovery. If management changes can be made for animals that are failing to thrive in a current situation, a more complete recovery may be possible and the welfare and economic costs of BRD may be minimized.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.776
GPT teacher head0.517
Teacher spread0.259 · 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