For tuberculosis elimination, Directly Observed Therapy, short course (DOTS) is essential but not sufficient
Bibliographic record
Abstract
Global tuberculosis (TB) incidence peaked in2004 (at 140/100,000/year) (1) and has declinedever so slightly since, but it is flourishing wherepoverty and marginalization abide, as in theCanadian Aboriginal communities referred to inthis issue of the Journal. Larcombe (2) describesthe crowded housing and inadequate ventilation, shown to be factors in TB transmission (3), in 2Aboriginal communities in Manitoba. While thisstudy does not causally link household crowdingto tuberculosis, it does describe woefully inadequatehousing, a marker of socio-economicdisparity common to Aboriginal communities ofCanada. Moreover, the study is a fine exampleof community-based participatory research inwhich a trusted researcher has been invited toinvestigate a community concern. The parametersof the information sought were determinedby the community itself. High participationresulted, and the findings were first discussedby the community as owners of the information, then published with their permission. Moresuch research is needed, and one hopes that itwill lead to meaningful outcomes — such as, inthis instance, improved housing, and perhapsreduced transmission of tuberculosis.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.012 | 0.023 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".