Bibliographic record
Abstract
SINGAPORE – Singapore eHealth Innovations Summit Announces the First EMRAM Stage 7 Hospital in Singapore and Emphasized Technology as Transformative Agent in Specialty Functions. TAIWAN – Health2Sync Strategically Partners with Taiwan's Ministry of Health and Welfare in Asia's First Government Supported Online Diabetes Care Program. UNITED STATES – Scientists Identify Protein Involved in Restoring Effectiveness of Common Treatment for Breast Cancer. UNITED STATES – Scientists Reveal How Signals from Pathogenic Bacteria Reach Danger Sensors of Cells. UNITED STATES – Scientists Find New Path in Brain to Ease Depression. UNITED STATES – Tips for Living a Heart Healthy Lifestyle. CANADA – Review Suggests Eating Oats Can Lower Cholesterol as Measured by a Variety of Markers. SOUTH KOREA – CSA Group Opens Highly Advanced Electro - Medical Laboratory in Seoul. AUSTRALIA – Cynata’s Technology Significant Efficacy in Preclinical Asthma Study. INDIA – Essilor Launches ‘Love to See Change’ Campaign to Educate People about Need to Preserve Visual Health.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.750 | 0.544 |
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".