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Evaluation of Rapid Identification Method for Mycobacterium tuberculosis Complex using the Immunochromatographic Slide Test Kit

2003· article· en· W2077551014 on OpenAlexaff
Miyuki Hasegawa, Etsuko KOYAMA, Utsuki Uchino, Yumie Sato, Intetsu Kobayashi, Katsu Saionji, Akira Watanabe

Bibliographic record

VenueKansenshogaku zasshi · 2003
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsTuberculosisMycobacterium tuberculosis complexMycobacterium tuberculosisSputumMicrobiologyHybridization probeBacteriaMycobacteriumLiquid cultureBiologyVirologyMedicinePathologyDNA

Abstract

fetched live from OpenAlex

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.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.391
Teacher spread0.285 · 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 designBench or experimental
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

Citations5
Published2003
Admission routes1
Has abstractyes

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