Are the Linnean and Phylogenetic Nomenclatural Systems Combinable? Recommendations for Biological Nomenclature
Bibliographic record
Abstract
A combination approach between the rules and recommendations from the Linnean (rank-based) and phylogenetic nomenclature is proposed, with a review of the debate. Advantages and drawbacks of both systems are discussed. Too often the debates are biased and unconstructive, and there is a need for dialogue and compromise. Our recommendations for the future of biological classification, to be considered by new editions of all codes of nomenclature, would enable the Linnean and the phylogenetic nomenclatural systems to coexist, or be combined. (1) We see it as essential that species binomen, including the formal rank of genus, are retained, and (2) species should continue to be linked to type specimens. (3) The use of other formal ranks should be minimized; however, we suggest retaining the classical supergeneric ranks (family, class, order, phylum, kingdom) for purely practical reasons. (4) For these ranks and any formally defined clades, type taxa (species, genera) should be replaced by phylogenetic definitions that explicitly hypothesize monophyly. (5) In contrast, species monophyly should not be required, because theory predicts that many species are not monophyletic. (6) It should be stressed that equal ranks do not imply comparable evolutionary histories.
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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 | 0.125 | 0.214 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.018 | 0.045 |
| Open science | 0.017 | 0.006 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.012 | 0.012 |
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".