Biodiversity2Drugs—Renaissance of exploring nature‐derived peptides for GPCR ligand discovery
Bibliographic record
Abstract
sponsorship: his research was funded by Biodiversa+, the European Biodiversity Partnership, in the context of the'Biodiversity2Drugs'project under the 2023-2024 BiodivNBSjoint call. It was co-funded by the European Commission (GA No. 101052342) and the following funding organisations: Fonds zur Forderung der wissenschaftlichen Forschung (Austria), Agence Nationale de la Recherche (France), Fonds Voor Wetenschappelijk Onderzoek-Vlaanderen (Belgium), Research Council of Norway (Norway), Dutch Research Council (The Netherlands), Brazilian National Council of State Funding Agencies & Brazilian National Council for Scientific and Technological Development (Brazil), Fonds de Recherche du Quebec (Canada), Innovation Fund Denmark (Denmark), Ministry of Universities and Research (Italy), Fundacao para a Ciencia e a Tecnologia, I.P. (Portugal), Agencia Estatal de Investigacion & Fundacion Biodiversidad (Spain), The Swedish Research Council for Environment, Agricultural, Sciences, and Spatial Planning (Sweden), and Swiss National Science Foundation (Switzerland); Austrian Science Fund (FWF), Grant/AwardNumber: 10.55776/PIN5093924. (Biodiversa+, European Biodiversity Partnership, European Commission|101052342, Fonds zur Forderung der wissenschaftlichen Forschung (Austria), Agence Nationale de la Recherche (France), Fonds Voor Wetenschappelijk Onderzoek-Vlaanderen (Belgium), Research Council of Norway (Norway), Dutch Research Council (The Netherlands), Brazilian National Council of State Funding Agencies & Brazilian National Council for Scientific and Technological Development (Brazil), Fonds de Recherche du Quebec (Canada), Innovation Fund Denmark (Denmark), Ministry of Universities and Research (Italy), Fundacao para a Ciencia e a Tecnologia, I.P. (Portugal), Agencia Estatal de Investigacion & Fundacion Biodiversidad (Spain), Swedish Research Council for Environment, Agricultural, Sciences, and Spatial Planning (Sweden), Swiss National Science Foundation (Switzerland), Austrian Science Fund (FWF)|10.55776/PIN5093924)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".