Patient management scenario: A framework for clinical decision and prognosis
Bibliographic record
Abstract
The depiction of prognosis is one of the main activities and a mainstay in medical practice. In cancer, as in other diseases, the prognosis differs for a variety of situations and evolves with time and with medical interventions. Although most commonly described at diagnosis, prognosis may be defined at any time during the course of the disease and for any endpoint including response to therapy, failure of treatment, survival, or preservation of function, and so forth. To facilitate the accurate portrayal of the future, the prognosis should be defined within a specific setting, referred to as a 'management scenario'. In the concept of a management scenario, the prognosis is defined using systematically considered prognostic factors, interventions and the outcome of interest. A deliberate and careful determination of prognosis is essential to clinical decision making and patient care. We illustrate the use of the concept of management scenario in several clinical examples.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".