Fungal Nomenclature at IMC10: Report of the Nomenclature Sessions
Bibliographic record
Abstract
Three Nomenclature Sessions were convened during the 10(th) International Mycological Congress (IMC10) in Bangkok on 3-8 August 2014. In addition a Questionnaire was given to all delegates. This Report reviews and summarizes the views expressed in the Sessions and in the responses to the Questionnaire. The issues covered related to aspects of: registration, protected names, forgotten names, pleomorphic fungi, lichenized fungi, typification, diagnoses, and governance. In addition, reports were received from working groups preparing lists of names to be proposed for protection, and controversial cases of competing names were discussed. The Congress was mandated to ratify decisions of the Nomenclature Committee for Fungi (NCF) on the appointment of repositories for the registration of new fungal names. After discussion in the Sessions on the decision of the NCF to appoint three such bodies, a Resolution to that effect was approved by the Congress. The Congress also adopted a Resolution asking that the opinions of mycologists on future directions for the nomenclature of fungi be taken into account in formulating changes in the rules for consideration at the International Botanical Congress in 2017.
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.
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 | 0.065 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.026 | 0.014 |
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".