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
BACKGROUND: Relative to radical nephrectomy (RN), partial nephrectomy (PN) performed for renal cell carcinoma (RCC) may protect from non-cancer-related deaths. The authors tested this hypothesis in a cohort of PN and RN patients. METHODS: The Surveillance, Epidemiology, and End Results-9 database allowed identification of 2198 PN (22.4%) and 7611 RN (77.6%) patients treated for T1aN0M0 RCC between 1988 and 2004. Analyses matched for age, year of surgery, tumor size, and Fuhrman grade addressed the effect of nephrectomy type (RN vs PN) on overall mortality (Cox regression models) and on non-cancer-related mortality (competing-risks regression models). RESULTS: Relative to PN, RN was associated with 1.23-fold (P = .001) increased overall mortality rate, which translated into a 4.9% and 3.1% absolute increase in mortality at 5 and 10 years after surgery, respectively. Similarly, non-cancer-related death rate was significantly higher after RN in competing-risks regression models (P < .001), which translated into a 4.6% and 4.5% absolute increase in non-cancer-related mortality at 5 and 10 years after surgery, respectively. CONCLUSIONS: Relative to PN, RN predisposes to an increase in overall mortality and non-cancer-related death rate in patients with T1a RCC. In consequence, PN should be attempted whenever technically feasible. Selective referrals should be considered if PN expertise is unavailable.
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 | 0.000 | 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) | 0.001 | 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 it