Organizational Guidance for the Care of Patients with Head-and-Neck Cancer in Ontario
Bibliographic record
Abstract
Background: At the request of the Head and Neck Cancers Advisory Committee of Ontario Health (Cancer Care Ontario), a working group and expert panel of clinicians with expertise in the management of head-and-neck cancer developed the present guideline. The purpose of the guideline is to provide advice about the organization and delivery of health care services for adult patients with head-and-neck cancer. Methods: . The guideline development methods included an updated literature search, internal review by content and methodology experts, and external review by relevant health care providers and potential users. Results: To ensure that all patients have access to the highest standard of care available in Ontario, the guideline establishes the minimum requirements to maintain a head-and-neck disease site program. Recommendations are made about the membership of core and extended provider teams, minimum skill sets and experience of practitioners, cancer centre-specific and practitioner-specific volumes, multidisciplinary care requirements, and unique infrastructure demands. Conclusions: The recommendations contained in this document offer guidance for clinicians and institutions providing care for patients with head-and-neck cancer in Ontario, and for policymakers and other stakeholders involved in the delivery of health care services for head-and-neck cancer.
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.
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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".