Characterization of clear cell - Renal cell carcinoma using neutrophil - Lymphocyte ratio
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
The features of tumour in clear cell - renal cell carcinoma are evaluated using neutrophil - lymphocyte ratio for its prognosis. Hence, 186 clear cell-renal cell carcinoma patients with documented neutrophil lymphocyte ratio were obtained. Depending on the features of the lesion, patients underwent either a partial or radical nephrectomy and characteristics were studied in relation to normal or high neutrophil - lymphocyte ratio with a cut-off of 2.7. Of the 186 patients studied, 131 had a normal neutrophil lymphocyte ratio (<2.7), while 55 presented with an elevated neutrophil lymphocyte ratio (≥2.7). Elevated neutrophil lymphocyte ratio was significantly associated with both tumor size and renal vein invasion, with a p-value of less than 0.001. Thus, the neutrophil lymphocyte ratio is a valuable metric for assessing renal vein extension and predicting tumour size.
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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