Bibliographic record
Abstract
C&EN has gathered the details about these rising stars of chemistry Average age: 34 Name Hometown Current town Chibueze Amanchukwu Lagos, Nigeria Chicago Ahmed Badran Tanta, Egypt, and Tucson, Arizona La Jolla, California Rachel Carter Nashville, Tennessee Washington, DC Rob Dennis-Pelcher Lyndonville, New York Green, Ohio Samantha M. Gateman Cambridge, Ontario London, Ontario Alisha Jones West Haven, Connecticut, and Toledo, Ohio New York City Outi Keinänen Espoo, Finland Birmingham, Alabama Sarah Lovelock Watford, England Manchester, England Jesus Moreno San Diego San Diego Nako Nakatsuka Tokyo Geneva Michael Skinnider Victoria, British Columbia Princeton, New Jersey Julian West Edmonton, Alberta Houston Peer-reviewed papers published: 353 Patents: 42 Includes provisional and regular patent applications. Languages spoken: 9 Arabic, English, Finnish, French, German, Igbo, Japanese, Norwegian, and Spanish Do you play an instrument or compete competitively in a sport (now or in the past)? Chibueze Amanchukwu: “Does being a DJ count as musical
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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.416 | 0.359 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".