Bibliographic record
Abstract
Although still young, the Journal of Pollination Ecology has established itself as a successful and vital conduit for research results, methodological advances, and—to some extent—opinion pierces concerning the diverse field of pollination biology. In a sense, it has been too successful, because the founding Editor-in-Chief, Carolin Mayer, has decided that she needs assistance in handling the increased volume of submissions and associated tasks. After deliberating, the board members of JPE have opted to try a new arrangement. I have accepted their invitation to join the effort as Editor-in-Chief, while Carolin’s title will switch to Managing Editor. She will retain responsibility for the essential operation and production of the journal, while I will take on ultimate responsibility for evaluating submissions, finding reviewers, and establishing the content of the journal. Of course, I will depend heavily on the Associate Editors in this effort.
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 | 0.011 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.106 | 0.111 |
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".