Cole Relaxation Frequency as a Prognostic Parameter for Breast Cancer
Bibliographic record
Abstract
We previously reported successful classification of breast cancer versus benign tissue using the Cole relaxation frequency measured on tissue excised during breast surgery as part of a study at two urban hospitals in the U.S. Midwest. Using that health system's cancer registry, we have discovered retrospectively that outcomes for patients who participated in the initial study can be classified correctly in 3 well-differentiated categories: nonrecurrent (NR); recurrent with no metastasis (RNM); and recurrent with metastasis (RM). As Cole relaxation frequency increases, the classification moves from NR to RNM and finally to RM. Multivariate analysis showed a significant association of "time-cancer-free" for all patients in these recurrent categories, with P-values ranging between 0.0001 to 0.0047. Thus, this follow-up report shows the potential feasibility of using Cole relaxation frequency as a prognostic parameter in a larger prospective study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".