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 Significant advances have been made over the past decade in the understanding of clinicopathologic prognostic factors for soft tissue sarcoma. Foremost among these advances is an improved ability to recognize the subset of patients at high risk for recurrent disease and tumor‐related death based on clinicopathologic data available at the time of initial presentation. Recent advances have also helped to elucidate specific molecular factors that have independent prognostic significance. This review summarizes the available data on traditional clinicopathologic, medical, and molecular prognostic factors for adult soft tissue sarcoma. Expected outcomes will be provided, drawing in particular from the results of a large series of patients managed at one center. Although there are many potential outcomes that could be assessed, the discussion will focus almost entirely on the traditional oncology outcomes of local control, metastatic risk, and survival. Other important outcomes, such as limb preservation; function, and quality of life will not be emphasized because of space limitations. The factors will be discussed in a framework that focuses on the tumor‐related , host‐related (or patient associated), and environment‐related background for these factors. The review will conclude with a summary tabulation identifying strata of the importance of factors to everyday clinical practice using the principles outlined in Chapter 2. These include essential factors (needed for treatment decision‐making), additional factors (of benefit for describing a cohort of patients), and new and promising factors that may of benefit in the future to exploit new treatment or diagnostic strategies.
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) | 0.064 | 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 it