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
Introduction: Lung metastasis is usually associated with poor outcomes in cancer patients. This study was performed to characterize and analyze the population of patients with de novo (synchronous) lung metastases using the Surveillance, Epidemiology and End Results (SEER) database. Materials and Methods: Baseline characteristics of lung metastasis patients were obtained from SEER case listings. Incidence rates and counts of synchronous lung metastasis were also obtained using the SEER * Stat software. Survival outcomes were analyzed using univariate and multivariable Cox regressions, controlling for confounders. An alpha threshold of 0.05 was used for statistical significance and p -values were subject to correction for multiple comparisons. Results: The age-adjusted incidence rate of synchronous lung metastasis was 17.92 per 100,000 between 2010 and 2015. Synchronous lung metastases most commonly arose from primary lung cancers, colorectal cancers, kidney cancers, pancreatic cancers and breast cancers. During this time period, 4% of all cancer cases presented with synchronous lung metastasis. The percentage of patients presenting with synchronous lung metastasis ranged from 0.5% of all prostate cancers to 13% of all primary lung cancers. The percentage of all cancer cases presenting with synchronous lung metastasis increased over time. De novo metastatic patients with lung metastases had worse overall survival [hazard ratio = 1.22 (1.21–1.23), p < 0.001] compared to those with only extrapulmonary metastases, controlling for potential confounders. Conclusions: Synchronous lung metastasis occurs frequently and is an independent predictors of poor patient outcomes. As treatment for lung metastases becomes more complicated, patients with synchronous lung metastasis represent a high-risk population.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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