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Record W117526451 · doi:10.1093/pch/5.2.81

World TB Day, March 24, 2000 – Forging new partnerships to stop TB

2000· article· en· W117526451 on OpenAlexaffabout
E. Lee Ford‐Jones, Ian Kitai, NE MacDonald

Bibliographic record

VenuePaediatrics & Child Health · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsSickKids FoundationDalhousie UniversityHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineTuberculosisPublic healthDiseaseDeveloping countryPopulationTransmission (telecommunications)Environmental healthPediatricsDemographyEconomic growthPathology

Abstract

fetched live from OpenAlex

Nearly 2000 years after Hippocrates described the “almost always fatal disease of the lungs” in 460 BC, tuberculosis (TB) is a global public health crisis (1). In the early 1800s, one in five Canadians had TB in their lifetime. As rates fell because of an improved standard of living, effective control of transmission by public health means and effective therapy, there were hopes for TB's eradication (although disease remained at unacceptable levels among the Aboriginal population) (2). In Canada, approximately 2000 new cases and more than 100 deaths are reported each year (2). The number of Canadians asymptomatically infected with the tubercle bacillus (ie, skin test positive) is unknown. Of those adults who become skin test positive (ie, infected), there is approximately a 5% risk in the year after they become skin test positive and another 5% risk over the rest of their lives that they will develop TB disease of the chest, nervous system, bone, abdomen, etc. For the young child, the risk of disease, as opposed to just infection, is increased to 40% in the first year after infection when the skin test becomes positive.

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)0.002
metaresearch head score (Gemma)0.003
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.099
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0990.049

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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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
GenreCommentary

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
Published2000
Admission routes2
Has abstractyes

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