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Record W202933170 · doi:10.1155/2012/297530

Reducing the Adverse Impact of Injection Drug Use in Canada

2012· article· en· W202933170 on OpenAlexaffabout
Kevin B. Laupland, John M. Embil

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of ManitobaUniversity of Calgary
Fundersnot available
KeywordsCriminalizationHarm reductionMedicineInjection drug useAdverse effectIntensive care medicineDrugPsychological interventionEnvironmental healthHarmPublic healthDrug injectionPsychiatryCriminologyPharmacologyPathologyLaw

Abstract

fetched live from OpenAlex

Injection of illicit drugs is a major health problem worldwide. There are currently an estimated 100,000 injection drug users in Canada (1). Infectious complications of injection drug use (IDU) include, but are not limited to, injection-related skin and soft tissue infection and abscesses, bloodstream infection and endocarditis, and infection by transmission of blood borne pathogens, such as HIV, hepatitis viruses and syphilis (2-4). In addition, IDU is associated with a general increased risk for infection such as with pneumonia and for acquisition of antimicrobial resistant organisms, most notably methicillin-resistant Staphylococcus aureus (5). Indirectly, IDU is associated with other behaviours and social circumstances that lead to further infectious disease risk and general adverse health consequences.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.012
GPT teacher head0.274
Teacher spread0.262 · 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 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

Citations7
Published2012
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Infectious Diseases and Medical MicrobiologySame topicHIV, Drug Use, Sexual RiskFrench-language works237,207