A human bone NOD/SCID mouse model to distinguish metastatic potential in primary breast cancers
Bibliographic record
Abstract
In this study, we created a clinically relevant model using NOD/SCID mice engrafted with human bone fragments in both right and left flanks, and show that the human bone implants are viable and functional for more than 6 mo. To investigate the growth and metastatic behavior of breast cancer, human primary breast tumor specimens were transplanted into human bone grafts under only the right flanks of the human-bone NOD/SCID mice. Some of the engrafted tumors proliferated extensively with massive neo-vascularization and also metastasized to the initially tumor-free left flank bone grafts. We show for the first time that this mouse model can be used to distinguish between primary breast tumors that do or do not proliferate and metastasize to contralateral human bone implants that were initially tumor-free.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".