Every sponge its own name: removing Porifera homonyms
Bibliographic record
Abstract
The occurrence of different sponge species bearing the same Linnean binomial name combination, i.e. homonyms, is to be avoided for obvious reasons. In a review of sponge taxon names of the World Porifera Database, we detected 121 homonymic cases (115 species-group names, 6 genus-group names), involving a total of 272 nominal taxa. It is the object of the present study to remove their occurrence by proposing new names for the junior homonyms following the rules of the International Commission of Zoological Nomenclature as laid down in the Code (ICZN, 1999) and the on-line edition http://iczn.org/iczn/index.jsp . Homonym cases are discussed and, where applicable, junior homonyms are either replaced by nomina nova or reassigned to their earliest available synonyms. The order in which the homonyms are treated is alphabetical on original species name, with genus names separately treated at the end. A summary table with all proposed name changes is also presented to allow quick access to the junior homonyms and their proposed new names. A total of 116 nomina nova are proposed, including five new genus names.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".