Cytokines and cell adhesion molecules exhibit distinct profiles in health, ovarian cancer, and breast cancer
Bibliographic record
Abstract
OBJECTIVE: We examined a panel of cytokines and cell adhesion molecules in an attempt to identify cancer specific profiles. DESIGN AND METHODS: Cytokines and cell adhesion arrays (Randox Ltd.) were measured in samples from women with a histological diagnosis of ovarian cancer ([Formula: see text]) or breast cancer ([Formula: see text]) or cancer free ([Formula: see text]). Random forest analysis was used for classification. RESULTS: Ovarian cancer subjects were classified with a sensitivity of 85.7% (95% CI 50-100) and a specificity of 84.2% (95% CI 69.4-93.4). Breast cancer subjects were classified with a sensitivity of 70.8% (95% CI 47.1-86.4) and a specificity of 96.4% (95% CI 82.1-100). DISCUSSION: Cytokine and cell adhesion molecule profiles provide additional information that may be useful for cancer characterization of female cancers.
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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) | 0.000 | 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 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".