Extracellular vesicles – vehicles that spread cancer genes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Once regarded as cellular 'debris' extracellular vesicles (EVs) emerge as one of the most intriguing entities in cancer pathogenesis. Intercellular trafficking of EVs challenges the notion of cancer cell autonomy, and highlights the multicellular nature of such fundamental processes as stem cell niche formation, tumour stroma generation, angiogenesis, inflammation or immunity. Recent studies reveal that intercellular exchange mediated by EVs runs deeper than expected, and includes molecules causative for cancer progression, such as oncogenes (epidermal growth factor receptor, Ras), and tumour suppressors (PTEN). The uptake of oncogenic EVs (oncosomes) by various cells may profoundly change their biology, signalling patterns and gene expression, and in some cases cause their overt tumorigenic conversion. Moreover, EVs circulating in blood and present in body fluids provide an unprecedented access to the molecular circuitry driving cancer cells, and new technologies are being developed to exploit this property as a source of unique cancer biomarkers.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it