Evaluation of Rapid Identification Method for Mycobacterium tuberculosis Complex using the Immunochromatographic Slide Test Kit
Bibliographic record
Abstract
Capilia TB, a lateral flow immunochromatographic slide test kit for directly identifying Mycobacterium tuberculosis complex (MTC), was evaluated by using culture-positive specimens from Mycobacteria Growth Indicator Tubes (MGIT). Sputum specimens from patients suspected of having tuberculosis were treated with NALC-NaOH and cultivated in MGIT960. Liquid specimens were collected from the positive tubes and directly inoculated with Capilia TB. Liquid specimens were also directly tested with AccuProbe. Of the organisms isolated from the 100 MGIT positive tubes, M. tuberculosis complex was identified in 49 (49%) tubes with Capilia TB and not identified in 51 (51%) with Capilia TB. Mycobacterium avium-intracellulare complex (MAC) was identified in 46 (46%) with AccuProbe MAC and other acid-fast bacteria were identified in 5 (5%) by DNA-DNA hybridization method. There were one tube in which M. tuberculosis complex was detected with Capilia TB and M. tuberculosis complex was not detected with AccuProbe MTC, but no tubes in which M. tuberculosis complex was detected with AccuProbe MTC and M. tuberculosis complex was not detected with Capilia TB. Capilia TB is excellent in sensitivity and specificity and very suitable for rapid diagnosis of tuberculosis and is considered to contribute to public health intervention measures taken for the tuberculosis control in Japan.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".