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
Depending on a variety of prognostic factors including age, stage, laboratory abnormalities, and initial response to treatment, from 70% to 90% of patients with advanced-stage Hodgkin lymphoma can be cured with modern multiagent chemotherapy. Two effective strategies offer the promise to improve on those results. Early intensification of treatment, typically by increasing the doses and frequency of administration of standard chemotherapy agents, induces higher initial response rates but has the major drawback of causing unacceptably severe acute toxicity, increased numbers of secondary neoplasms, and infertility due to oligospermia in men and premature menopause in women. Alternatively, integration of novel therapeutic agents into primary treatment is attractive, especially when the introduction not only improves the frequency and durability of disease response but also does not unacceptably increase acute or long-term toxicity. Finally, widespread availability of functional imaging with positron emission tomography now enables response-adapted therapy, a separate innovation in the treatment of Hodgkin lymphoma that can be incorporated with either intensified chemotherapy or addition of novel agents. This article discusses these exciting new developments in the treatment of advanced-stage Hodgkin lymphoma.
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 | 0.001 |
| 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