The Importance of Prognosis in Cancer Medicine
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
Abstract Prognostic judgment remains an essential element of modern, medical practice. It meets patients' needs for information about the future that they can use to plan their lives, and it provides a basis for rational medical decisions. In the future, the importance of prognosis in oncology is likely to increase as new predictors of the prognosis permit increasingly accurate predictions of the outcomes of treatment. Over the last 30 years, advances in clinical epidemiology have greatly improved the practice of oncology; we understand much better today how to establish the “generalizability” of clinical observations. In future, however, the challenge will be to increase the “particularizability” of medical knowledge in such a way that the individual characteristics of the patient and the tumor are appropriately factored into treatment decisions. This will require characterizing patients, not only in terms of the diagnostic group to which they belong, but also in terms of all those individual characteristics that may influence the outcome of treatment. Hence, the importance of continuing to study prognostic factors in oncology, and learning to use them correctly.
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) | 0.001 | 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) | 0.001 | 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