Review of Recent Advances in Fluorescence Bronchoscopy in Early Localization of Central Airway Lung Cancer
Bibliographic record
Abstract
Centrally located lung cancers are radiologically occult until so far advanced as to have a low cure rate or require extensive resection for cure, but at a cost of high morbidity. These cancers represent about one-fifth of new lung cancers. Autofluorescence bronchoscopy appears to be an important tool in localizing premalignant and early malignant lesions in the large central airways, particularly when applied to high-risk patients. Applications include studies of molecular biology of premalignancy and early malignancy, chemoprevention studies, endobronchial therapy studies, localization of synchronous tumors, estimation of the extent of field cancerization, and better estimation of resection margins. Autofluorescence bronchoscopy appears to be significantly more sensitive than white light examination but has low specificity. This technology is likely to gain widespread use when evaluation of sputum for malignant changes is both more sensitive and specific, and when its application is demonstrated to reduce mortality in this important subgroup of non-small cell lung cancer patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".