Abstract 4819: Assessing the environmental factors in two Ontario communities with diverging colorectal cancer incidence rates .
Bibliographic record
Abstract
Abstract Colorectal cancer is the third most diagnosed cancer and second leading cause of cancer related deaths in Canada. As Ontario has the largest population in Canada, it also has great disparities in colorectal cancer incidence. The region of Timiskaming has the highest incidence for colorectal cancer, while the region of Peel has the lowest incidence for colorectal cancer in Ontario. There are no previously published studies regarding cancer or environmental risk factors performed in the Timiskaming region. The purpose of this study was to identify the dominant non-nutritional modifiable environmental risk factors in the region of Timiskaming compared to the reference region of Peel that may be associated with diverging colorectal cancer incidence rates. After reviewing the available published literature, a questionnaire assessment tool regarding environmental exposures was created. This questionnaire tool was created by combining standardized questionnaire tools available in the published literature that assessed environmental exposures. The questionnaire assessment tool was then utilized within a pilot study group followed by the Timiskaming and Peel participant communities. The tool assessed the exposures of tobacco smoking, alcohol use, pesticides/organochlorines, metal toxins, occupational exposures, and medical ionizing radiation. A total of 53 participants completed the questionnaire tool in Timiskaming, and a total of 61 participants completed the questionnaire tool in Peel. Findings indicate that there are dominant non-nutritional modifiable environmental risk factors in the region of Timiskaming that may be associated with colorectal cancer when compared to the region of Peel. The significant dominant environmental factors identified by Timiskaming participants were tobacco smoking, alcohol use, pesticides/organochlorines, and metal toxins. The findings also indicate that the Peel community may have important community health initiatives that can be used in the Timiskaming community to reduce the present colorectal cancer disparities. Following this study, it is imperative that recommendations are directed at a community level and relate to the assessment of potential non-nutritional modifiable environmental risk factors. While colorectal cancer disparities are evident, future research should help to understand the relationship between cancer disparities and environmental risk factors. Citation Format: Jeavana Sritharan, Rishikesan Kamaleswaran, Ken McFarlan, Manon Lemonde, Clemon George, Otto Sanchez. Assessing the environmental factors in two Ontario communities with diverging colorectal cancer incidence rates . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4819. doi:10.1158/1538-7445.AM2013-4819
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".