The rise of evo‐devo: Pan‐American Society for Evolutionary Developmental Biology sets the stage
Bibliographic record
Abstract
rst meeting on the Clark Kerr campus of the University of California, Berkeley.Th e Society emerged as an outcome of a 2013 NSF-funded workshop organized by Dr. Cassandra Extavour (Harvard University) and Dr. Allen Rodrigo (NESCent).Th e goal of the workshop was to explore and defi ne the future of evolutionary developmental biology (evodevo) as an integrative scientifi c discipline, with its own specifi c intellectual goals and biological questions, and to defi ne initiatives to advance collaborative research, education, infrastructure development, training and outreach related to furthering the study of evo-devo ( Moczek et al., 2015 ).Th e society was offi cially established during this workshop, with a mission to promote the study of evo-devo in all organisms and provide a forum for establishing tools for collaboration, communication, and education in the fi eld of evo-devo and a commitment to excellence, equity, and diversity.Th e fi rst meeting-organized by the Society's President Ehab Abouheif, Vice President Karen Sears, and local organizers Nipam Patel and Chris Lowe-served to further this mission and highlight this commitment.Th e meeting, which was attended by 163 faculty, 59 postdoctoral researchers, and 106 student members of the Society, was organized around a strong lineup of invited speakers-an international group of men and women who are engaged in research investigating the foundations of developmental evolution from both theoretical and experimental perspectives.Th e presented research incorporated diverse organisms, and the speakers spanned all career stages.Th is meeting was one of the fi rst where the "plant" and "animal" researchers did not retreat to their own sessions, but rather talks fl owed seamlessly.Topics included the evolution of gene regulatory networks, evolution of form and function, and patterning and plasticity in plants, invertebrates, and vertebrates; evolution of multicellular and unicellular organisms; and developmental
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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 | 0.019 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".