The Alberta moving beyond breast cancer (AMBER) cohort study: baseline description of the full cohort
Bibliographic record
Abstract
Abstract Purpose The Alberta Moving Beyond Breast Cancer (AMBER) Study is an ongoing prospective cohort study investigating how direct measures of physical activity (PA), sedentary behavior (SB), and health-related fitness (HRF) are associated with survival after breast cancer. Methods Women in Alberta with newly diagnosed stage I (≥ T1c) to IIIc breast cancer were recruited between 2012 and 2019. Baseline assessments were completed within 90 days of surgery. Measurements included accelerometers to measure PA and SB; a graded treadmill test with gas exchange analysis to measure cardiorespiratory fitness (VO2peak); upper and lower body muscular strength and endurance; dual-X-ray absorptiometry to measure body composition; and questionnaires to measure self-reported PA and SB. Results At baseline, the 1528 participants’ mean age was 56 ± 11 years, 59% were post-menopausal, 62% had overweight/obesity, and 55% were diagnosed with stage II or III disease. Based on device measurements, study participants spent 8.9 ± 1.7 h/day sedentary, 4.4 ± 1.2 h/day in light-intensity activity, 0.9 ± 0.5 h/day in moderate-intensity activity, and 0.2 ± 0.2 h/day in vigorous-intensity activity. For those participants who reached VO2peak, the average aerobic fitness level was 26.6 ± 6 ml/kg/min. Average body fat was 43 ± 7.1%. Conclusion We have established a unique cohort of breast cancer survivors with a wealth of data on PA, SB, and HRF obtained through both direct and self-reported measurements. Study participants are being followed for at least ten years to assess all outcomes after breast cancer. These data will inform clinical and public health guidelines on PA, SB, and HRF for improving breast cancer outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".