Non-melanoma Skin Cancer in Canada Chapter 1: Introduction to the Guidelines
Bibliographic record
Abstract
BACKGROUND: Non-melanoma skin cancer (NMSC), including basal and squamous cell carcinoma, represents the most common malignancy. OBJECTIVE: The aim of this document is to provide guidance to Canadian health care practitioners on NMSC management. METHODS: After conducting a literature review, the group developed recommendations for prevention, management, and treatment of basal cell carcinomas, squamous cell carcinomas, and actinic keratoses. These tumour types are considered separately in the accompanying articles. The Grading of Recommendations Assessment, Development and Evaluation system was used to assign strength to each recommendation. RESULTS: This introduction describes the scope and structure of the guidelines and the methods used to develop them. The epidemiology of NMSC is reviewed, as are the pathophysiologic changes occurring with damage to the skin, which lead to the formation of actinic keratoses and invasive squamous or basal cell carcinomas. CONCLUSIONS: This introduction describes the need for primary prevention and offers an overview of treatment options that are discussed in later chapters of the guidelines.
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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".