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Record W2395387724

Transmission characteristics of tuberculosis in the foreign-born and the Canadian-born populations of Alberta, Canada.

2004· article· en· W2395387724 on OpenAlexaffabout
Dennis Kunimoto, K Sutherland, Kate Wooldrage, Anne Fanning, Linda Chui, Jure Manfreda, Richard Long

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineGynecologyPulmonary tuberculosisLung diseaseHumanitiesTuberculosisInternal medicineArtPathology
DOInot available

Abstract

fetched live from OpenAlex

SETTING: All notified cases of tuberculosis in the province of Alberta, Canada, 1994-1998. OBJECTIVE: To compare the transmission characteristics of tuberculosis among foreign-born and Canadian-born cases. DESIGN: Retrospective analysis using DNA fingerprinting (IS6110 restriction fragment length polymorphism and spoligotyping) and patient information from the Alberta Tuberculosis Registry. Transmission indexes were determined by calculating the average number of culture-positive pulmonary cases generated by a single source case. RESULTS: Of the 750 cases of active tuberculosis, 437 (58.3%) were in the foreign-born. DNA fingerprinting of Mycobacterium tuberculosis isolates from all 573 culture-positive cases over the 5 years from 1994 to 1998 showed that there was significantly less clustering among foreign-born isolates (9.8%) compared to Canadian-born non-Aboriginal (28.8%) and Aboriginal (44.7%) isolates. The transmission index was significantly higher for males, lower for those > or =65 years of age, and higher for Aboriginals. CONCLUSION: Although cases of tuberculosis in the foreign-born constitute the majority in Alberta, there is little transmission to other foreign-born or to Canadian-born individuals. Transmission of tuberculosis among the Aboriginal population remains a significant problem in Alberta.

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)0.001
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 score0.185
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.027
GPT teacher head0.263
Teacher spread0.237 · 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

Citations48
Published2004
Admission routes2
Has abstractyes

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