Closing the Gap on the Availability of Cancer Staging Information for Healthcare Providers in the Global Cancer Community: Development of a Multilingual Cancer Staging Video Series
Bibliographic record
Abstract
Background and context: Tumor, Node, Metastases (TNM) classification system provide valuable measures to researchers in facilitating the understanding of disparities in outcomes and allowing for the comparison of these outcomes over time. There is a lack of multimodal formats for disseminating comprehensive information and education about cancer stage to the global cancer community. To address this gap, the Departments of Radiation Oncology and Cancer Education at the Princess Margaret Cancer Centre (PM) (Toronto, Canada) in collaboration with The Union for International Cancer Control (UICC) envisioned the development of a cancer staging video series. Aim: To provide current and accurate information on cancer staging to healthcare professionals and stakeholders for global cancer control. Strategy/Tactics: The Cancer Education program worked with experts in the field of cancer staging to develop 8 videos (average length 4 min) to provide information to the global cancer community about existing information on key issues with cancer staging and how to properly stage patients using the TNM classification. Videos include references to current research and examples of staging across various cancers to illustrate and reinforce the importance of cancer staging. Script development involved defining key messages, refining learning objectives and breaking up information to ensure the content is digestible and easy to understand. Prior to video production, draft scripts were reviewed by international collaborators for completeness of information and accuracy of content. Videos contain appropriate text on screen to reinforce key messages and include a narrated voiceover to orient the learner. To expand the global reach, trained faculties translated the English videos and scripts, into the 5 official United Nations languages: Arabic, Chinese, French, Russian and Spanish. Program/Policy process: Videos in the cancer staging series include: The Importance of Cancer Staging; What is Cancer Stage; General Rules for Cancer Staging; Cancer Staging Examples; Staging Terminology; Importance of a Common Stage Language; Why Stage Language Changes; Essential TNM. Videos will be made available on UICC and PM Web sites (free of charge and globally advertised). Outcomes: The video series will increase education and awareness on the importance of a unified approach to cancer staging among the larger community and have the aim to empower the community on how to access cancer and define prognosis, treatment and or trial eligibility. What was learned: The development and promotion of the cancer staging video series was a meaningful, collaborative and challenging activity. It was learned that educational videos need to be well-designed and simple to provide axiomatic information on cancer stating to the global cancer control community.
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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".