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Record W2130357399 · doi:10.3168/jds.2012-6359

Development and implementation of a training program to ensure high repeatability of body condition scoring of dairy cows

2013· article· en· W2130357399 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

VenueJournal of Dairy Science · 2013
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaUniversity of British ColumbiaDairy Farmers of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesUniversité de SherbrookeMinistère de l'Agriculture, des Pêcheries et de l'AlimentationNovalaitUniversité Laval
KeywordsRepeatabilityMilkingTrainerAnimal scienceDairy cattleKappaCohen's kappaMathematicsStatisticsOperations managementComputer scienceBiologyEngineering

Abstract

fetched live from OpenAlex

A body condition score (BCS) in dairy cattle is a subjective assessment of the proportion of body fat that she possesses and is a common measure used in animal welfare assessment. The objectives of our study were to develop and implement a training program to produce highly repeatable BCS by many assessors as part of a cross-Canada epidemiological study on dairy cow comfort and welfare. In preliminary studies, we established that without any proper standard operating procedures (SOP) to describe the practical steps of the process and good standard reference for each score, assessors provided with a BCS chart scored with each other only with substantial agreement within 0.5 points and moderate agreement on exact score (mean weighted kappa coefficient=0.79 and 0.46, respectively). Detailed SOP were developed to assess BCS in 4 locations on a dairy farm. Assessing BCS presented more challenges in some locations (when cows exited the milking parlor, when the assessor was located outside the freestall pen) than others (when cows were headlocked at the feed bunk, when assessor was located inside the freestall pen). Additionally, training material and a training procedure were developed to ensure that future assessors would achieve almost perfect repeatability with the trainer within 0.5 points (weighted kappa coefficient >0.80). Twelve trainees followed this training and their repeatability was assessed using photographs in classroom sessions and live observations on farm over a 1-wk period. Repeatability was maintained above target agreement at periodic checks over the 6 mo of on-farm data collection. Two trainers were used as a reference standard to which all trainees were compared. This study demonstrates that to obtain reliable measures, a training program must include validated procedures to help assessors cope with a variety of farm setups. Regular repeatability checks are essential to ensure that the reference standard is maintained over time and to secure high data quality. This method to develop a training program as well as the training program implemented can be used as a model to successfully train on-farm assessors.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.072
GPT teacher head0.385
Teacher spread0.312 · 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