Near-infrared Raman spectroscopy detects lung cancer
Bibliographic record
Abstract
This work was to explore near-infrared (NIR) Raman spectroscopy for distinguishing tumor from normal bronchial tissue. A rapid NIR Raman system was used for tissue Raman studies. High-quality Raman spectra in the 700-1800 cm-1 range can be acquired from human bronchial tissues in vitro. Raman spectra differed significantly between normal and malignant tumor tissue, with tumors showing increased nucleic acid, tryptophan, phenylalanine signals and decreased phospholipids, proline, and valine signals than normal tissue. Raman spectral shape differences between normal and tumor tissue were also observed particularly in the spectral ranges of 1000-1100, 1200-1400, and 1500-1700 cm-1, which are related to the protein and lipid conformations and CH stretching modes in nucleic acids. The ratio of Raman intensities at 1445 cm-1 to 1655 cm-1 provided good differentiation between normal and malignant bronchial tissue, suggesting that NIR Raman spectroscopy may have a significant potential for the noninvasive diagnosis of lung cancer in vivo based on optical evaluation of biomolecules.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".