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Record W2120028391 · doi:10.1186/2047-2994-1-6

Control of antimicrobial resistance in Canada: any lessons to learn?

2012· article· en· W2120028391 on OpenAlexafffundabout
Lindsay E. Nicolle

Bibliographic record

VenueAntimicrobial Resistance and Infection Control · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversity of ManitobaManitoba HealthHealth Sciences Centre
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsAntibiotic resistancePublic healthAgency (philosophy)MedicineResistance (ecology)Drug resistanceInfection controlCorporate governanceEnvironmental healthBusinessIntensive care medicinePathologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Over the past 15 years, repeated national meetings have developed recommendations for a Canadian antimicrobial resistance strategy. Despite this, in 2011 there is no comprehensive, integrated national program with appropriate governance and funding to address antimicrobial resistance. FINDINGS: The Public Health Agency of Canada supports a reference laboratory for diagnosis and characterization of selected resistant strains, targeted surveillance programs which monitor resistance trends for selected animal and human organisms, development of national infection control guidelines including for antimicrobial resistant organisms, and a few local pilot projects to address community acquired MRSA. Sporadic programs of variable intensity and quality are supported by some provinces, health regions and individual facilities but these are not comprehensive, standardized or integrated. Individual researchers and research groups, however, have published substantial information describing the prevalence and impact of resistance in Canada. CONCLUSIONS: Current review of activities by the Public Health Agency of Canada and initiatives by the National Coordinating Centre for Infectious Diseases may move the country forward in developing an effective national approach to address antimicrobial resistance.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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.

Study designBench or experimental
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
Published2012
Admission routes3
Has abstractyes

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