Bibliographic record
Abstract
INDIA – Lack of access to technology ‘hampers detection of substandard drugs’. JAPAN – Daiichi Sankyo announces development of nucleic acid treatment for Duchenne muscular dystrophy utilizing proprietary technology. SINGAPORE – IBN creates unlimited source of human kidney cells. SINGAPORE – Dyesol and Singapore's NTU sign agreement. THE PHILIPPINES – Global biotech/GM crop plantings increase 100-fold from 1996. AUSTRALIA – Phosphagenics further expands pain portfolio. AUSTRALIA – Primary Health Care signs Australia distribution agreement for iGeneScreen™ prenatal test. AUSTRALIA – Folic acid in pregnancy linked with reduced autism risk. AUSTRALIA – Phylogica and Bio-Link collaborate to commercialize anti-inflammatory Phylomers. AUSTRALIA – ABRAXANE ® plus gemcitabine improves survival in Phase III study of patients with advanced pancreatic cancer. CANADA – Verisante Technology, Inc. announces first sales of aura, a revolutionary medical device for the detection of skin cancer. EUROPE – Project eyes robust medical technology for poor countries. UNITED KINGDOM – Asthma sufferers have more lung fungi. UNITED KINGDOM – Pioneering drug discovery gets major funding to move to next stage. UNITED STATES – Gilead's sofosbuvir for hepatitis C meets primary endpoint in fourth pivotal Phase III study. UNITED STATES – Eleven Biotherapeutics publishes data on EBI-005, a novel IL-1 inhibitor protein for topical treatment of dry eye disease. UNITED STATES – Phase I/II trial of ADXS-HPV in anal cancer conducted by Brown University Oncology Group. UNITED STATES – Scopolamine: An old drug with new psychiatric applications. UNITED STATES – New bioengineered ears look and act like the real thing. UNITED STATES – To trap a rainbow, slow down light. UNITED STATES – AB SCIEX responds to milk contamination concerns with new method to detect dicyandiamide.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.765 | 0.629 |
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".