Characterization and discrimination of nasopharyngeal carcinoma and nasopharyngeal normal cell lines using confocal Raman microspectroscopy
Bibliographic record
Abstract
Raman microspectroscopy can provide molecular-level information about the biochemical composition and structure of cells and tissues with excellent spatial resolution. In this study, Raman spectroscopy of individual cells from nasopharyngeal carcinoma cell lines C666-1, CNE2 and nasopharyngeal normal cell line NP69 are investigated for their differences. The spectral intensity ratio at 1449 and 1657 cm−1with a decision line of I1449/I1657=1.10 can very easily separate the tumor and normal cell lines into two groups. Principal component analysis (PCA) and linear discriminant analysis (LDA) are also used to classify different cell lines and achieved a specificity and sensitivity of 100 and 90%, respectively. The results support the potential utility of Raman spectroscopy for nasopharyngeal diagnosis.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".