Guidelines for interpreting the International Code of Nomenclature of Prokaryotes and for preparing a Request for an Opinion
Bibliographic record
Abstract
In this paper the Judicial Commission provides general guidance for interpreting the International Code of Nomenclature of Prokaryotes (ICNP) and specific assistance to authors, reviewers and editors of a Request for an Opinion, or of other suggestions related to the ICNP. The role of the Judicial Commission is recapitulated, particularly with respect to the processing of such Requests. Selected kinds of nomenclature-related proposals are discussed that are unsuitable as the basis for a Request. Particular emphasis is put on Requests for placing names or epithets on the list of nomina rejicienda , and a dichotomous identification key is provided to guide potential authors of a Request that targets the name of a species or subspecies because of issues with its type strain. To this end, the criteria for the valid publication of such names under the ICNP are revisited. Aspects of other kinds of Requests are also addressed. The study is based on a comprehensive review of all Judicial Opinions issued since the publication of the Approved Lists in 1980. One goal of this paper is to assist potential authors in deciding whether their concern should be the subject of a Request, and if so, in composing it with the greatest chance of success. It is also clarified how to obtain additional help regarding nomenclature-related issues.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".