Bibliographic record
Abstract
We thank Trivanovic et al for sharing their institutional experience of 83 patients with carcinoma of unknown primary, in which performance status (PS) was a more powerful prognostic factor than the presence of liver metastasis.. We and others investigators have previously demonstrated that PS was a powerful adverse clinical prognostic factor1-3 in the setting of carcinoma of unknown primary site. In our univariate analysis of 370 patients, short survival was related more strongly to PS (P < .0001) than to the presence of liver metastasis (P = .001).1 However, the presence of liver metastasis and low serum albumin levels were the most powerful adverse prognostic factors on multivariate analysis, which led us to develop and publish our new prognostic model. This new prognostic model outperforms the previous prognostic model based on PS and serum lactate dehydrogenase (LDH) levels.3 This improvement in prognostic accuracy is because of the high rate of elevated LDH in patients who are classified as good-risk in our model. Larger prospective studies, including both clinical and biologic parameters, are warranted now to validate our prognostic model. Although we agree with Trivanovic et al that PS may used to guide chemotherapy treatment decisions, we previously reported that factors other than PS carry greater weight in the decision to use chemotherapy.2 Pascal Seve MD*, John Hanson MD , John R. Mackey MD , * Department of Internal Medicine, Hospices Civils de Lyon and University Claude Bernard, Lyon, France, Department of Oncology, University of Alberta, Edmonton, Alberta, Canada.
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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 | 0.004 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.017 | 0.027 |
| Insufficient payload (model declined to judge) | 0.018 | 0.015 |
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".