Diversity, Nomenclature, and Taxonomy of Protists
Bibliographic record
Abstract
The new classification of protists from the International Society of Protistologists (Adl et al., 2005) could not apply both the International Code of Botanical Nomenclature and the International Code of Zoological Nomenclature because the two are incompatible. The classification designated one name for each clade where multiple names from different codes had previously existed, traced authorities, and provided a classification based on nameless ranks. Here we review important issues that remain to be resolved. Current rules governing validation of new species, from various codes of nomenclature, have become an impediment to naming of new protists. Standard requirements for protist species descriptions and type specimens need to be modernized to accommodate the rapid discovery of new species made possible by modern microscopic and molecular techniques. Although we agree with the criticisms of the botanical and zoological codes made by proponents of the Phylocode, we did not all agree that the current Phylocode is the solution, nor does it currently address species typification. Accordingly, new guidelines are needed to govern standards in protist species descriptions and classification.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".