Distinguishing and grading human gliomas by IR spectroscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As a molecular probe of tissue composition, IR spectroscopy can potentially serve as an adjunct to histopathology in detecting and diagnosing disease. This study demonstrates that cancerous brain tissue (astrocytoma, glioblastoma) is distinguishable from control tissue on the basis of the IR spectra of thin tissue sections. It is further shown that the IR spectra of astrocytoma and glioblastoma affected tissue can be discriminated from one another, thus providing insight into the malignancy grade of the tissue. Both the spectra and the methods employed for their classification reveal characteristic differences in tissue composition. In particular, the nature and relative amounts of brain lipids, including both the gangliosides and phospholipids, appear to be altered in cancerous compared to control tissue. Using a genetic classification approach, classification success rates of up to 89% accuracy were obtained, depending on the number of regions included in the model. The diagnostic potential and practical applications of IR spectroscopy in brain tumor diagnosis are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it