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Record W4377140177 · doi:10.3390/ani13101664

Inter-Rater Reliability of Scoring Systems for Abomasal Lesions in Quebec Veal Calves

2023· article· en· W4377140177 on OpenAlexafffundabout
Laura Van Driessche, Gilles Fecteau, Julie Arsenault, Léa Miana, Younès Chorfi, M. Villettaz Robichaud, Pierre Hélie, Sébastien Buczinski

Bibliographic record

VenueAnimals · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicReliability and Agreement in Measurement
Canadian institutionsUniversité de Montréal
FundersMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsInter-rater reliabilityLesionMedicineKappaConcordanceInternal medicineSurgeryStatisticsMathematicsRating scale

Abstract

fetched live from OpenAlex

The objective of this study was to determine the inter-rater reliability of current scoring systems used to detect abomasal lesions in veal calves. In addition, macroscopic lesions were compared with corresponding histological lesions. For this, 76 abomasa were retrieved from veal calves in a slaughterhouse in Quebec and scored by four independent raters using current scoring systems. The localisations of the lesions were separated into pyloric, fundic, or torus pyloricus areas. Lesions were classified into three different types, i.e., erosions, ulcers, and scars. To estimate the inter-rater reliability, the coefficient type 1 of Gwet’s agreement and Fleiss κ were used for the presence or absence of a lesion, and the intra-class correlation coefficient was used for the number of lesions. All veal calves had at least one abomasal lesion detected. Most lesions were erosions, and most of them were located in the pyloric area. Overall, a poor to very good inter-rater agreement was seen for the pyloric area and the torus pyloricus regarding the presence or absence of a lesion (Fleiss κ: 0.00–0.34; Gwet’s AC1: 0.12–0.83), although a higher agreement was observed when combining all lesions in the pyloric area (Fleiss κ: 0.09–0.12; Gwet’s AC1: 0.43–0.93). For the fundic area, a poor to very good agreement was also observed (Fleiss κ: 0.17–0.70; Gwet’s AC1: 0.90–0.97). Regarding the inter-rater agreement for the number of lesions, a poor to moderate agreement was found (ICC: 0.11–0.73). When using the scoring system developed in the European Welfare Quality Protocol, a poor single random rater agreement (ICC: 0.42; 95% CI: 0.31–0.56) but acceptable average random rater agreement (ICC: 0.75; 95% CI: 0.64–0.83) was determined. Microscopic scar lesions were often mistaken as ulcers macroscopically. These results show that the scoring of abomasal lesions is challenging and highlight the need for a reliable scoring system. A fast, simple, and reliable scoring system would allow for large scale studies which investigate possible risk factors and hopefully help to prevent these lesions, which can compromise veal calves’ health and 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.

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)0.008
metaresearch head score (Gemma)0.004
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 score0.063
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.224
GPT teacher head0.408
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2023
Admission routes3
Has abstractyes

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