Bibliographic record
Abstract
Average age: 33 Number of language spoken: 9 (Dutch, English, French, German, Korean, Mandarin, Polish, Portuguese, Spanish) Number of peer-reviewed papers published: 353 Number of patents filed: 13 Journeys Here are the locales our 12 have called home then and now Darryl Boyd: Kalamazoo, Mich. Morgan Cable: Titusville, Fla. Connor Coley: Columbus, Ohio Pedro García Barrantes: San José, Costa Rica Nicole Gaudelli: Rochester, N.Y. Roxanne Kieltyka: Toronto, Ontario Joseph Moran: Montreal, Quebec Cathy Mulzer: Hopewell Junction, N.Y. Mónica Pérez-Temprano: Valladolid, Spain Jose Rodriguez: Los Angeles, Calif. Luisa Whittaker-Brooks: Colón, Panama Y. Shrike Zhang: Nanjing, China the latest TV shows they’ve binge-watched Even extraordinary chemists need a brain break every once in a while Darryl Boyd: “Luke Cage” and “Riverdale” Morgan Cable: “Dark Matter” Connor Coley: “Westworld” Pedro García Barrantes: “The Walking Dead” and spin-off “Fear the Walking Dead” Nicole Gaudelli: “Mozart in the Jungle” Roxanne Kieltyka: “Chef’s Table” Joseph Moran:
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.570 | 0.570 |
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".