Pre-treatment platelet counts as a prognostic and predictive factor in stage II and III rectal adenocarcinoma
Bibliographic record
Abstract
AIMTo investigate if pre-treatment platelet counts could provide prognostic information in patients with rectal adenocarcinoma that received neo-adjuvant treatment. METHODSPlatelet number on diagnosis of stage II and III rectal cancer was evaluated in 51 patients receiving neoadjuvant treatment and for whom there were complete follow-up data on progression and survival, as well as pathologic outcome at the time of surgery.Pathologic responses on the surgical specimen of patients with lower platelet counts (150-300 × 10 9 /L) were compared with these of patients with higher platelet counts (> 300 × 10 9 /L) by the χ 2 test.Overall and progression free survival Kaplan-Meier curves of the two groups were constructed and compared with the Log-Rank test. RESULTSA significant difference was present between the two groups in regards to pathologic response with patients with lower platelet counts being more likely to exhibit a Retrospective
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".