Bibliographic record
Abstract
SINGAPORE – NUS Researchers Uncover Potent Parasite-killing Mechanism of Nobel Prize-Winning Anti-Malarial Drug. SINGAPORE – Robotic Glove Invented by NUS Researchers Helps Patients Restore Hand Movements. UNITED STATES – Study Reveals Environment, Behavior Contribute to Some 80 Percent of Cancers. UNITED STATES – Probing the Mystery of How Cancer Cells Die. UNITED STATES – Liver Hormone Works Through Brain's Reward Pathway to Reduce Preference for Sweets & Alcohol. UNITED STATES – How Three Genes You've Never Heard of May Influence Human Fertility. UNITED STATES – Researchers Find Link between Processed Foods and Autoimmune Diseases. UNITED KINGDOM – Is Evolution More Intelligent Than We Thought? UNITED KINGDOM – Unravelling the Genetics of Pregnancy and Heart Failure. SWITZERLAND – New Global Framework to Eliminate Rabies. CANADA – Droughts Hit Cereal Crops Harder Since 1980s. TAIWAN – Discovery of Key Autophagy Terminator that Contributes to Cell Survival and Muscle Homeostasis.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.780 | 0.579 |
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".