Cohort profile: The Forzani & MacPhail Colon Cancer Screening Centre biorepository, Calgary, Alberta
Bibliographic record
Abstract
PURPOSE: The Colon Cancer Screening Centre (CCSC) biorepository (Calgary, Canada) supports a wide range of research topics related to colorectal cancer (CRC) by collecting, and storing biospecimens (blood, urine, normal colon tissue) from consenting patient participants. Housing unique biospecimens along with detailed participant lifestyle and health history questionnaire data, the CCSC biorepository can support a variety of research related to CRC risk factors, biomarkers, genetic causes and more. PARTICIPANTS: Currently, 2292 average risk CRC patients have consented to participate in the CCSC cohort and have provided stored biospecimens. The collected samples and data provide important high-quality materials for research, discovery and evaluation related to CRC screening and carcinogenesis and is available for access by outside researchers. In addition to biological samples, the CCSC collects detailed patient information on their lifestyle, physical activity and dietary patterns through questionnaires at the time of their enrolment. FINDINGS TO DATE: (overweight), 53% having never smoked tobacco and 13% having a family member with CRC. FUTURE PLANS: The CCSC cohort plans to include the recruitment of high risk CRC cohorts. High-risk participants would comprise patients with a positive faecal immunochemical test and family history of CRC.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.073 | 0.019 |
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".