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Record W6906574153 · doi:10.17605/osf.io/4nw8r

Describing frameworks that may be adapted to a Canadian national surveillance of antimicrobial resistance from dogs & cats: Scoping review protocol

2022· other· en· W6906574153 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Public health surveillanceDisease surveillanceAntibiotic resistanceEpidemiological surveillanceHealth surveillanceDisease control

Abstract

fetched live from OpenAlex

This scoping review will assess the literature to 1) identify existing systems or frameworks for antimicrobial resistance (AMR) surveillance from companion animals, 2) review the feasibility of these existing systems for a Canadian national program for surveillance of AMR from companion animals, and 3) identify existing disease surveillance systems for companion animals that could be adapted for Canadian national surveillance of AMR from these species. Addressing gaps in AMR surveillance from companion animals is essential in working towards a comprehensive One Health approach to addressing the overall issue of AMR in Canada.

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)0.202
metaresearch head score (Gemma)0.233
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.914
Threshold uncertainty score0.984

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2020.233
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0070.016
Bibliometrics0.0380.036
Science and technology studies0.0080.005
Scholarly communication0.0120.010
Open science0.0090.016
Research integrity0.0110.007
Insufficient payload (model declined to judge)0.0520.012

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 head0.175
GPT teacher head0.418
Teacher spread0.242 · 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.

Study designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2022
Admission routes1
Has abstractyes

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