Bibliographic record
Abstract
Glioblastoma multiforme (GBM) is one of the most malignant human tumors, with a uniformly poor outcome. One obstacle in curing malignant brain tumors is the limitation of conventional light microscopy in detecting microscopic residual tumor in biopsy samples from the perimeter of the surgically resected tumor. We further refined the identification of GBM tumor tissue at the sub-cellular level, utilising the technique of Synchrotron, sourced mid-infrared (mid-IR) spectromicroscopy. Paired, thin (5 microm) cryosections of snap-frozen human GBM tumor samples removed at elective surgery were mounted on glass slides (hematoxylin and eosin-stained tissue section) and calcium fluoride (CaF2) windows (unstained tissue section for transmission spectromicroscopy), respectively. Concordance of tumor bearing areas identified in the stained section with the unstained IR tissue section was confirmed by the pathologist of the study. Compared with molecular signatures obtained from normal control brain tissue, unique spectroscopic patterns were detected in GBM tumor samples from 6 patients. The identifying features of GBM were: i) high protein-to-lipid ratios (amide I+II/CH2 symmetric stretch; amide I+II/CH2+CH3 symmetric and asymmetric stretch), and ii) considerable enhancement of the intensities of characteristic peaks at 2,957 and 2,871 cm(-1) representing CH3 asymmetric and symmetric stretch, respectively. Spectral data sets were subjected to Ward's algorithm for assignment to similar groups, and then subjected to hierarchical cluster analysis (HCA) by means of false color digital maps. False color images of 5 clusters obtained by HCA identified dominant clusters corresponding to tumor tissue. Corroboration of these findings in a larger number of GBM may allow for more precise identification of these and other types of brain tumors.
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How this classification was reachedexpand
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) | 0.002 | 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 teacher head, 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".