Clonality of localized and metastatic prostate cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: The influence of the long life-history of prostate cancer on the temporal and spatial variability of the tumour genome is now being elucidated. Multiregion sequencing to identify spatio-genomic differences in prostate tumour mutation profiles combined with computational approaches can map the evolution and transit of tumour cells throughout an individual patient. RECENT FINDINGS: A series of recent studies have demonstrated that a prostate tumour is often composed of different subclones, with varying genetic similarity. As such, a single biopsy specimen may be insufficient to make accurate clinical predictions from molecular biomarkers, greatly complicating the application of biopsy-based tools for precision medicine. In addition, subclones that arise outside of the primary tumour can seed new metastases and circulate between sites within a patient. SUMMARY: The mutational complexity of multiple tumour clones within the same individual, which respond differently to specific treatments, suggests the need for multimodal interventions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".