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Record W2752122335 · doi:10.3138/jammi.1.3.01

Northern tropics? Seven cases of pyomyositis in northwestern Ontario

2017· article· en· W2752122335 on OpenAlexaffvenueabout
Kassandra Loewen, Michael Kirlew, Paul Benvenuto, Neety Panu, Anukul Panu, Natalie Bocking, Len Kelly

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2017
Typearticle
Languageen
FieldMedicine
TopicInfectious Diseases and Tuberculosis
Canadian institutionsMcGill University Health CentreNOSM University
Fundersnot available
KeywordsPyomyositisMedicineIncidence (geometry)PopulationComorbidityDemographicsRetrospective cohort studyPediatricsDemographySurgeryInternal medicineEnvironmental healthAbscess

Abstract

fetched live from OpenAlex

OBJECTIVE: To document the incidence and clinical characteristics of (tropical) pyomyositis in a predominantly First Nations population in northwestern Ontario. METHODS: The present study was a retrospective case series conducted over a 38-month period in a population of 29,105 in northwestern Ontario. RESULTS: The authors identified seven cases of pyomyositis and describe demographics, comorbidity, clinical course, and the results of imaging and microbiology investigations. The incidence of pyomyositis in northwestern Ontario is 7.6 cases per 100,000 person-years, a rate that is approximately 15 times higher than the only published incidence rate for a developed country (Australia). CONCLUSION: The rate of pyomyositis is high. It may be mediated by overcrowded housing, inadequate access to clean water, and high background rates of methicillin-resistant Staphylococcus aureus infection, injection drug use, and type 2 diabetes mellitus.

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)0.001
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 score0.283
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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

Citations3
Published2017
Admission routes3
Has abstractyes

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