Limitations of Chest Radiography in Diagnosing Subclinical Pulmonary Tuberculosis in Canada
Bibliographic record
Abstract
that does not cause TB-related symptoms but does cause other abnormalities that can be detected using existing radiologic and mycobacteriologic assays." In high-income countries, subclinical PTB is usually diagnosed during active case finding, is acid-fast bacilli smear negative, and associated with minimal or no lung parenchymal abnormality on chest radiograph. In the absence of symptoms, the epidemiologic risk of TB and chest radiograph are critical to making the diagnosis. In a cohort of 327 patients with subclinical PTB, we address the question-how well field radiologists perform at identifying features important to the diagnosis of PTB, the presence or absence of which have been established by a panel of expert radiologists? Although not performing badly compared with this "gold standard," field readers were nevertheless susceptible to overread or underread films and miss key diagnostic features, such as the presence of a lung parenchymal abnormality, typical pattern, or cavitation. In the context of active case finding during which most patients with subclinical PTB are discovered, limitations of the chest radiograph need to be recognized, and sputum, ideally induced, should be submitted regardless of the radiographic findings.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".