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Half a century of research on cattle foot and claw diseases: a scientometric analysis

2019· article· en· W2996045466 on OpenAlexaboutno aff
Danilo Conrado Silva, Paulo José Bastos Queiroz, Pedro Augusto Cordeiro Borges, Ana Carolina Barros da Rosa Pedroso, Emmanuel Arnhold, Alex Silva da Cruz, Aparecido Divino da Cruz, Luiz Antônio Franco da Silva

Bibliographic record

VenueSemina Ciências Agrárias · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsnot available
FundersRazi Vaccine and Serum Research InstituteConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsHoofClawWeb of scienceSubject (documents)ScopusVeterinary medicineLibrary scienceFoot (prosody)BibliometricsMedicineGeographyMeta-analysisPathologyPolitical scienceBiologyMEDLINEArtComputer scienceAnatomy

Abstract

fetched live from OpenAlex

The objective of this study was to quantitatively evaluate scientific publications on cattle foot and claw diseases using the Scopus database. A combination of keywords "hoof disease AND bovine OR cattle OR cow" was used. Publications were classified according to the type, language, subject area, source title, author, affiliation, and country/territory. The documents were grouped later into thematic topics. The diseases evaluated in each study were quantified separately and in related groups, and distributed by decades. The frequencies of the thematic topics and diseases were compared by the chi-square test for adherence. In total, 642 publications were analyzed (595 articles, 46 reviews, and 1 note). Most of these papers were written in English (518). The main subject areas were Veterinary; Agricultural and Biological Sciences; and Biochemistry, Genetics, and Molecular Biology. Journal of Dairy Science was the journal that published most articles in the area, with the best citations (SCImago Journal Rank = 1.21). The authors with the highest number of publications were Johann Kofler with 19, and David Nixon Logue and Jan Keith Shearer with 18 documents each. By affiliation, the institution with the highest number of publications was the Swedish University of Agricultural Sciences. By country or territory, the United States of America (22%), the United Kingdom (17%), Germany (11%), and Canada (10%) together accounted for 60% of the publications. The classification of the documents into thematic topics resulted in four groups: Specific hoof diseases (70%), General hoof diseases (14%), Lameness (11%), and Healthy hoof characterization (5%). Eighteen foot and claw diseases have been studied, with the following being the most frequent: digital dermatitis (17%), sole ulcer (15%), and white line disease (11%). When grouped, laminitis-related diseases represented 48% and infectious diseases represented 38% of the studies. Overall, just over half a century of research on cattle foot and claw diseases, bovine digital dermatitis is the most studied disease. Grouping related disorders revealed that laminitis-related diseases are being studied more than infectious diseases since the 1980s, from when studies on individual foot diseases in cattle increased to the detriment of studies that aimed to evaluate them as a unique problem. Our study, the first scientometric analysis in the subject area, compiles valuable information that can help researchers to develop future projects.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.393
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.006
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 head0.045
GPT teacher head0.320
Teacher spread0.275 · 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

Labeled directly by 2 models reading the full record.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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