Onco-nephrology: a decalogue: Table 1.
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
Onco-nephrology is an evolving subspecialty that focuses on the complex relationships existing between kidney and cancer. In this opinion piece, we propose a 'decalogue of onco-nephrology', in order to highlight the areas where the nephrologist and oncologist should work closely over the ensuing years to provide cutting-edge care for patients afflicted with cancer and kidney disease. The 10 points we have highlighted include (1) acute kidney injury and chronic kidney disease in cancer patients; (2) nephrotoxic effects of anticancer therapy, either traditional chemotherapeutics or novel molecularly targeted agents; (3) paraneoplastic renal manifestations; (4) management of patients nephrectomized for a kidney cancer; (5) renal replacement therapy and active oncological treatments; (6) kidney transplantation in cancer survivors and cancer risk in ESRD patients; (7) oncological treatment in kidney transplant patients; (8) pain management in patients with cancer and kidney disease, (9) development of integrated guidelines for onco-nephrology patients and (10) clinical trials designed specifically for onco-nephrology. Following these points, a multidisciplinary onco-nephrology team will be key to providing outstanding, cutting-edge care in both the acute and chronic setting to these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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