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Record W2888852196 · doi:10.14745/ccdr.v40is2a01

Antimicrobial resistance and use in Canada: A federal framework for action

2014· article· en· W2888852196 on OpenAlexfundvenueaboutno aff

Bibliographic record

VenueCanada Communicable Disease Report · 2014
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchHealth CanadaPublic Health Agency of CanadaAgriculture and Agri-Food CanadaCanadian Food Inspection Agency
KeywordsGovernment (linguistics)Resistance (ecology)Stewardship (theology)BusinessWork (physics)Antimicrobial stewardshipAction (physics)Public relationsAntibiotic resistancePublic healthPolitical scienceMedicinePoliticsEngineeringNursing

Abstract

fetched live from OpenAlex

Antimicrobial resistance (AMR) is a serious and growing global public health threat. Modern medical and veterinary practice depends on the widespread availability of effective antimicrobials to prevent and treat infections in humans and animals. Addressing the growing threat of AMR in Canada is a shared responsibility; Antimicrobial Resistance and Use in Canada: A Federal Framework for Action serves as a starting point for a collaborative response. The goal of the Framework is: "To protect Canadians from the health risks related to antimicrobial resistance." It includes three pillars: Surveillance, Stewardship, and Innovation. The Framework identifies concrete Government of Canada actions to reduce the threat and impact of AMR. Equally important, it is a vehicle to engage partners and stakeholders in discussions on efforts that, together, can significantly increase the results of individual actions. Beyond the Government of Canada, provinces and territories, academia, animal and human health professionals, food production stakeholders, animal producer groups and farmers, as well as private industry each hold essential levers to reduce AMR. By continuing to work together, we will collectively achieve greater results in reducing the risks of antimicrobial resistance and protecting the health and safety of all Canadians.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.241
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.039
GPT teacher head0.297
Teacher spread0.257 · 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

Citations29
Published2014
Admission routes3
Has abstractyes

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