MétaCan
Menu
Back to cohort
Record W4214942759 · doi:10.3168/jdsc.2021-0153

Case-control study of behavior data from automated milk feeders in healthy or diseased dairy calves

2022· article· en· W4214942759 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJDS Communications · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
FundersCanada First Research Excellence Fund
KeywordsDisease controlAnimal scienceDiseaseDairy cattleDairy industryAllowance (engineering)BiologyBovine respiratory diseaseMedicineVeterinary medicineBiotechnologyFood scienceInternal medicineImmunology

Abstract

fetched live from OpenAlex

Group housing of preweaning dairy calves is increasing in popularity throughout the dairy industry. However, it can be more difficult to individually monitor calves to identify disease in these group systems. Automated milk feeders (AMF) not only provide producers with the opportunity to increase the milk allowance offered to preweaning calves but they can also monitor individual feeding behaviors that could identify calves at increased risk of disease. The objective of this retrospective case-control study was to determine how feeding behaviors change in preweaning calves leading up to and during a disease bout. This study was conducted between fall 2015 and fall 2016 on 2 commercial dairy farms in Ontario, Canada. Producers' treatment records for respiratory or enteric illness were used to identify cases. Control calves were selected from calves not treated for disease and matched on the days on the AMF. Both farms housed calves in dynamic groups of 9 to 11 calves with an AMF and fed milk replacer. Differences in feeding behaviors, including milk consumption, drinking speed, rewarded visits, unrewarded visits, and total visits to the AMF per day, were analyzed by mixed models accounting for repeated measures. Data were analyzed for the 7 d before, the day of, and 7 d after treatment. A total of 28 cases and 28 control calves (n = 56) were analyzed. Calves with disease consumed significantly less milk than their healthy counterparts, beginning 5 d before disease and until 3 d after disease detection. Sick calves had fewer unrewarded visits starting 3 d before until 2 d after illness detection. Sick calves drank significantly more slowly starting 4 d before illness detection until the day after illness detection compared with healthy controls. No differences were found between cases and controls for rewarded visits. Calves on a high plane of milk nutrition significantly alter feeding behaviors before illness detection. Data from AMF on feeding behaviors may help to detect disease earlier in preweaning dairy calves.

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 score0.192
Threshold uncertainty score0.981

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.279
GPT teacher head0.456
Teacher spread0.177 · 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