Cybertaxonomy to accomplish big things in aphid systematics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biodiversity sciences have progressed at such a pace that the taxonomic community has been unable to grow concomitantly to keep up with the influx of biological data. This "taxonomic impediment" has led some to suggest that taxonomy is no longer pertinent and to the development of methodologies that circumvent the taxonomic process. This article does not seek to argue for the importance of taxonomy but rather is a call to the aphid taxonomy community to rise to the challenge by dramatically increasing the volume and comprehensiveness of its output without sacrificing quality. Recent informatics technology allows us to mobilize the 2 most important aphid taxonomy resources: experts and specimens, both distributed globally. "Cyberspecimens," museum specimens digitally rendered at a resolution sufficient for remote identification, and open "cybertaxonomic" tools will allow the international aphid taxonomic community to carry out large, ambitious, projects. The global aphid cybertaxonomy proposed here will serve not only the ends of research aphidologists, but also provide a model for other taxonomic communities to adapt and adopt as we confront both the taxonomic impediment and the taxonomic naysayers.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it