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Record W2796087561 · doi:10.4212/cjhp.v71i1.1730

Funding for Antimicrobial Stewardship Programs: A Customizable Business Case Template

2018· article· en· W2796087561 on OpenAlexaffvenue
Nicole Le Saux, Bruce Dalton, Kim Abbass, John Conly, Nick Daneman, Linda Dresser, Sergio Fanella, Greg J. German, Jennifer Grant, Yoav Keynan, Tim T Y Lau, Jamie McDonald, Caroline Nott, David M. Patrick, Yvonne Shevchuk, Daniel J. G. Thirion, Andrew M. Morris

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversité de MontréalUniversity of SaskatchewanSunnybrook Health Science CentreBC Centre for Disease ControlHealth Sciences CentreUniversity Health NetworkOttawa HospitalUniversity of ManitobaUniversity of CalgaryVancouver General HospitalChildren's Hospital of Eastern OntarioNova Scotia Health AuthorityAlberta Health Services
Fundersnot available
KeywordsAntimicrobial stewardshipStewardship (theology)BusinessProcess managementKnowledge managementEngineering managementBusiness administrationComputer sciencePolitical scienceEngineeringChemistryAntibiotic resistanceAntibiotics

Abstract

fetched live from OpenAlex

1

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)0.032
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.003
Science and technology studies0.0040.003
Scholarly communication0.0120.008
Open science0.0050.009
Research integrity0.0130.006
Insufficient payload (model declined to judge)0.0420.010

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 head0.032
GPT teacher head0.280
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2018
Admission routes2
Has abstractyes

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