Bibliographic record
Abstract
SINGAPORE – Intelligent Sensor Informs You to Change a Diaper via SMS JAPAN – Tokyo Institute of Technology research: Key genetic event underlying fin-to-limb evolution ISRAEL – Independent Results Show that BiondVax's Universal Flu Vaccine Administered in a Trial 3 Years ago Improves Immunogenicity against Current Flu H3N2 Epidemic UNITED KINGDOM – Imperial Innovations Launches Orthonika: A Novel Knee Meniscus Replacement UNITED KINGDOM – New Vaccine For Chlamydia to Use Synthetic Biology CANADA – Aeterna Zentaris Announces Data and Safety Monitoring Board Scheduled to Complete Second Interim Analysis of the ZoptEC Phase 3 Trial in Endometrial Cancer in Early October UNITED STATES – NueMD Launches Free ICD-10 Training Tool Ahead of October 1 Deadline UNITED STATES – A new hope for Moderate and Severe Dementia: Upsher-Smith receives FDA approval for generic version of Namenda (Memantine HCL) Tablets UNITED STATES – FDA Approves U.S. Product Labeling Update for Sprycel ® (dasatinib) to Include Five-Year First-Line and Seven-Year Second-Line Efficacy and Safety Data in Chronic Myeloid Leukemia in Chronic Phase
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.738 | 0.643 |
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".