Bibliographic record
Abstract
Breast cancer is the number one cancer of women in the world. In middle income countries, and in many low income countries, breast cancer has become the most frequent cancer in women, supplanting cancer of the cervix. In such countries, breast cancer is usually diagnosed at an advanced stage, the majority in stage III and IV, indicating substantial delay in diagnosis. Further, because of the age distribution of the population pyramid, the majority of breast cancers are diagnosed in women under the age of 50. However, that age distribution does not mean that breast cancer is a different disease than in the West. Where population-based cancer registry data are available, it becomes clear that the individual risk for women at every age is no greater than in the West, and in many countries much less. Zusammenfassung Brustkrebs ist die Krebsart, die bei Frauen weltweit an erster Stelle steht. In Staaten mittleren Wohlstandes und in einigen Staaten geringeren Wohlstandes wurde Brustkrebs bei Frauen zur häufigsten Krebsart und hat somit den Krebs der Zervix verdrängt. In solchen Ländern wird Brustkrebs üblicherweise im fortgeschrittenen Stadium diagnostiziert, hauptsächlich im Stadium III und IV, was zu einer erheblichen Verzögerung der Diagnosestellung führt. Des Weiteren wird aufgrund der Altersverteilung in der Bevölkerungspyramide, die Mehrzahl der Brustkrebserkrankungen bei Frauen unter 50 Jahren diagnostiziert. Wie auch immer, diese Alters-Strukturen bedeuten nicht, dass Brustkrebs eine andere Erkrankung als im Westen ist. Wo Datenaufzeichnungen von Krebserkrankten geführt werden, wird schnell deutlich, dass das individuelle Risiko für Frauen jeden Alters nicht größer ist als im Westen und in vielen Ländern viel geringer.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".