Data from Identification of a Stat3-Dependent Transcription Regulatory Network Involved in Metastatic Progression
Bibliographic record
Abstract
Abstract High levels of activated Stat3 are often found in human breast cancers and can correlate with poor patient outcome. We employed an activated ErbB2 mouse model of breast cancer to investigate the in vivo role of Stat3 in mammary tumor progression and found that Stat3 does not alter mammary tumor initiation but dramatically affects metastatic progression. Four-fold fewer animals exhibited lung metastases in the absence of Stat3 and a 12-fold reduction in the number of lung lesions was observed in animals bearing Stat3-null tumors when compared with the wild-type cohort. The decreased malignancy in Stat3-deficient tumors is attributed to a reduction in both angiogenic and inflammatory responses associated with a Stat3-dependent transcriptional cascade involving CCAAT/enhancer binding protein δ. [Cancer Res 2009;69(17):6823–30]
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.015 | 0.003 |
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".