Risk of nontuberculous mycobacterial pulmonary disease with obstructive lung disease
Bibliographic record
Abstract
Nontuberculous mycobacterial pulmonary disease (NTM-PD) is increasingly prevalent [1] and especially common in the elderly [2]. It is usually chronic, requiring complex therapy with suboptimal outcomes [3]. Risk factors for NTM-PD may be covert, presumably disordered mucociliary defences, or overt structural lung abnormalities. In one study, 56% of NTM-PD patients had unexplained nontuberculous mycobacteria (NTM) and among the rest with structural lung disease, chronic obstructive pulmonary disease (COPD) was the most common predisposing condition [4]. High incidence of NTM pulmonary disease in people with COPD and asthma (142 and 53 per 100 000 person-years) Datasets used in this study were linked using unique encoded identifiers and analysed at ICES. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions and statement expressed herein are those of the author, and not necessarily those of CIHI.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".