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Record W4312242888 · doi:10.3406/bavf.2022.71005

Nutrition enrichie et nutraceutiques dans l’arthrose canine : une revue systématique et une méta-analyse en 2022

2022· article· fr· W4312242888 on OpenAlexaff
Maude Barbeau-Grégoire, Antoine Cournoyer, Colombe Otis, Maxim Moreau, Bertrand Lussier, Eric Troncy

Bibliographic record

VenueBulletin de l Académie vétérinaire de France · 2022
Typearticle
Languagefr
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsCentre Hospitalier de l’Université de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsGynecologyMedicinePhilosophyHumanitiesPolitical science

Abstract

fetched live from OpenAlex

Le but de cette revue systématique et métanalyse était d’examiner les évidences d’efficacité clinique analgésique des diètes enrichies et nutraceutiques testés chez des chiens arthrosiques. À partir de quatre bases de données bibliographiques électroniques, 1096 publications ont été retracées, en plus de 20 publications provenant de sources internes. Cinquante-quatre articles ont été inclus, comprenant 69 essais et permettant d’établir 9 catégories de traitement. L’évaluation d’efficacité, modulée par le niveau de qualité des essais, établit une évidence analgésique, avec effet clinique, pour les diètes enrichies et les suppléments à base d’oméga-3, ainsi que ceux à base de cannabidiol (à moindre degré). Nos analyses démontrent aussi une faible efficacité du collagène, et un non-effet marqué des nutraceutiques à base de chondroïtine – glucosamine qui nous pousse à recommander que ces derniers produits ne soient plus conseillés pour la gestion des douleurs en arthrose canine.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.028
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.059
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.018
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.021
GPT teacher head0.306
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBulletin de l Académie vétérinaire de FranceSame topicVeterinary Orthopedics and NeurologyFrench-language works237,207