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Record W1775839798 · doi:10.1155/2000/156183

′Pseudo′ Treatment Failure of Pulmonary Tuberculosis in Association with a Tuberculoma

2000· article· en· W1775839798 on OpenAlexafffund
Richard Long, Sylvia Chomyc, Evelina Der, Daniel Sitar

Bibliographic record

VenueCanadian Respiratory Journal · 2000
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of ManitobaCapital District Health AuthorityUniversity of Alberta
FundersUniversity of Alberta
KeywordsMedicineTuberculomaTuberculosisPulmonary tuberculosisMEDLINEInternal medicineRadiologySurgeryPathology

Abstract

fetched live from OpenAlex

Failure of tuberculosis patients to respond to treatment is usually explained by one or more of five mechanisms: improper drug prescription; patient nonadherence to prescribed therapy; primary or acquired drug resistance; drug malabsorption; and rarely, exogenous reinfection with a drug-resistant isolate. Response to treatment is best measured bacteriologically; two different smear and one culture criteria for failure are widely used. Patients meeting either smear, but not culture, criteria for treatment failure may be said to have 'pseudo' treatment failure. Whether a patient can meet both smear criteria for failure, and not have a mechanism for treatment failure nor meet culture criteria, is unknown. A case of 'pseudo' treatment failure is reported in which both smear criteria for failure were met, but no mechanism for failure was proven to be operative.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.019
GPT teacher head0.276
Teacher spread0.257 · 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 designCase report
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

Citations1
Published2000
Admission routes2
Has abstractyes

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