A cancer survivorship model for holistic cancer care and research
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
Advancements in cancer have increased survival rates leading to a paradigm shift such that cancer is considered a chronic disease, necessitating an evaluation of our understanding of cancer survivorship (CS). For this purpose, a comprehensive literature search was performed, using CINAHL, MEDLINE, and PUBMED from 2000-2021. Drawing from the concepts in the literature, salient factors that affect CS across cancer populations were identified and a proposed model was developed. This paper describes the Cancer Survivorship Model (CSM). The CSM represents predisposing factors for survivors and survivorship's acute, extended, and long-term phases, influencing factors: treatment and maintenance (medical/ psychosocial care), well-being, influencing aspects (life-changing experience, uncertainty, prioritizing life, wellness management, and collateral damage), and social relationship factors that impact survivors' symptom burdens and overall survivorship experience (health outcomes and quality of life). A case study demonstrates the CSM utility. Future application of the model holds promise for improving the quality of survivorship and informing research and clinical practice to promote and optimize survivors' outcomes throughout the evolving survivorship.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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