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
Tumors shed DNA, proteins, other molecules, and cells into the bloodstream long before they can be spotted with techniques like magnetic resonance imaging. A new liquid biopsy approach could help diagnose brain cancer earlier by detecting those molecules in a tiny blood sample ( ACS Nano 2022, DOI: 10.1021/acsnano.2c04187 ). It relies on an ultrasensitive nanosensor that can amplify the Raman vibrational signal of cancer biomarkers present in blood at extremely low concentrations. Researchers used the method to distinguish brain tumors from other types of cancer and determine a brain tumor’s general location. “Blood tests are a lot easier and less expensive than imaging,” says Bo Tan, an engineer at Toronto Metropolitan University who led the new study. And unlike conventional biopsies of brain tissue, they would not require a surgical procedure to get a sample. But liquid-based cancer tests developed up to this point rely on amplifying small amounts
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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