The Faculty of 1000 Biology Factor Will Revolutionize Scientific Evaluation and Publishing
Bibliographic record
Abstract
F1000 Biology is the brainchild of Vitek Tracz, the chairman of Current Science Group. It was founded in 2002 as a means to “highlight and review the most interesting papers published in the biological sciences, based on the recommendations of a faculty of well over 1000 selected leading researchers” – more than 1600 scientists in fact. The entire field of biology is divided into 16 subject areas (called Faculties), each presided over by several Heads of Faculty and comprised of a panel of Faculty Members that “[involves] both experienced and younger investigators” and is inclusive of all nationalities and genders. The Members are encouraged to evaluate and rank two to four published articles of significant scientific merit every month. The rankings from all Members are compiled and an “F1000 Factor” is calculated for each article. Comments are also posted with the rankings (1).
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 | 0.097 | 0.299 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.030 | 0.017 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.120 | 0.101 |
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".