Abstract withdrawn
Bibliographic record
Abstract
The emphasis of mammographic breast screening is to detect small invasive breast cancers at a time in their natural history when early detection and treatment will reduce significantly the risk of death. However, breast screening cannot be absolutely specific in its approach and detects a wide spectrum of breast cancer, ranging from microfocal low-grade ductal carcinoma in situ to large highgrade invasive cancer. It is well recognized that many of the lowgrade, special invasive cancers identified at screening have an excellent prognosis but may be so indolent that they would never have presented clinically or have threatened the life of the patients. It has been proposed alternatively that a proportion of these low-grade invasive tumours might, if not detected, de-differentiate over time into more aggressive, less well-differentiated tumours. Identification and removal of such cancers when they are at a low grade would avoid such progression. Detection of high-grade invasive cancers when they are small is clearly a means by which screening could reduce breast cancer mortality; for example, the Two-County Trial in Sweden has shown that histological grade 3 invasive cancers detected when <10 mm have an excellent prognosis, while it is widely recognized that large high-grade invasive cancers have a poor prognosis. In addition, the presence of vascular invasion and lymph node metastasis, which are associated with development of metastatic disease, are rare in grade 3 tumours <10 mm, grade 2 tumours <10 mm and grade 1 tumours <20 mm, indicating that detecting tumours under a certain size should be beneficial.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".