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
AUSTRALIA – Australian Scientists in Stem-cell First. AUSTRALIA – Australia's First SynCardia Total Artificial Heart Implant. AUSTRALIA – First Patient Receives Gamma Knife Treatment in Australia. AUSTRALIA – ADHD Pesticide Link Confirmed. AUSTRALIA – Aged Garlic Extract can lower Blood Pressure. CHINA – Chinese Scientists Discover Liver Cancer-prone Genes. CHINA – Experts Find Gene Variants for Stomach, Gullet Cancer. CHINA – China Publishes List of 33 Circulating Fake Medicines. CHINA – Chinese Vaccine Shields against Hepatitis E. INDIA – Genetic Cause of Gall Bladder Stones Found. INDIA – Obesity Surgery can Reverse Metabolic Complications. INDIA – Japanese Encephalitis on Rise in India. NEW ZEALAND – Rising Cases of Swine Flu in NZ. SINGAPORE – New Hope for Women with Breast or Ovarian Cancer. SINGAPORE – Singapore on Alert for Gene that Creates Superbugs. SINGAPORE – NCCS to Lead Asian Phase III Clinical Trial for Colorectal Cancer. SINGAPORE – A*STAR and Institut Mérieux/Biomérieux Invest S$3m in Tuberculosis Research. SINGAPORE – International Conference on Bioengineering and Nanotechnology to Boost Interdisciplinary Research. SINGAPORE – Scientists to Research Ways to Fight Infectious Diseases and Viruses. TAIWAN – Chang Gung Team Develops New Brain Cancer Treatment. TAIWAN – Taiwan, Canada Develop New Hepatitis C Screening Method.
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 | 0.000 | 0.000 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it