Bibliographic record
Abstract
INDIA – Bioven starts BV-NSCLC-001 Phase III trial in NSCLC. INDIA – Initiative in Chemical Biology and Therapeutics. PHILLIPPINES – Asia–Pacific Analysis: The slow road to green energy. SINGAPORE – Takeda progressing well in Asia with New Drug Applications. SINGAPORE – NTU and University of Warwick boost brainpower in global neuroscience research. THAILAND – Thai PhD. student awarded Monsanto's Beachell–Borlaug International Scholarship for rice improvement research. EUROPE – Open access will change the world, if scientists want it to. UNITED STATES & CANADA – Verisante places Aura Beta Units for safety, verification testing in B.C., Alberta and Ontario clinics. UNITED STATES & CANADA – Life Technologies sets new worldwide standard for criminal forensic testing with introduction of GlobalFilerTM Express Kit. UNITED STATES & CANADA – How immune cells can nudge nerves to regrow. UNITED STATES & CANADA – Improved Genomic Target Selection Using IDT Oligos. UNITED STATES & CANADA – US team uncover non-invasive method for diagnosing epilepsy.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.735 | 0.506 |
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".