The Faces of Fungi database: fungal names linked with morphology, phylogeny and human impacts
Bibliographic record
Abstract
Taxonomic names are key links between various databases that store information on different organisms. Several global fungal nomenclural and taxonomic databases (notably Index Fungorum, Species Fungorum and MycoBank) can be sourced to find taxonomic details about fungi, while DNA sequence data can be sourced from NCBI, EBI and UNITE databases. Although the sequence data may be linked to a name, the quality of the metadata is variable and generally there is no corresponding link to images, descriptions or herbarium material. There is generally no way to establish the accuracy of the names in these genomic databases, other than whether the submission is from a reputable source. To tackle this problem, a new database (FacesofFungi), accessible at www.facesoffungi.org (FoF) has been established. This fungal database allows deposition of taxonomic data, phenotypic details and other useful data, which will enhance our current taxonomic understanding and ultimately enable mycologists to gain better and updated insights into the current fungal classification system. In addition, the database will also allow access to comprehensive metadata including descriptions of voucher and type specimens. This database is user-friendly, providing links and easy access between taxonomic ranks, with the classification system based primarily on molecular data (from the literature and via updated web-based phylogenetic trees), and to a lesser extent on morphological data when molecular data are unavailable. In FoF species are not only linked to the closest phylogenetic representatives, but also relevant data is provided, wherever available, on various applied aspects, such as ecological, industrial, quarantine and chemical uses. The data include the three main fungal groups (Ascomycota, Basidiomycota, Basal fungi) and fungus-like organisms. The FoF webpage is an output funded by the Mushroom Research Foundation which is an NGO with seven directors with mycological expertise. The webpage has 76 curators, and with the help of these specialists, FoF will provide an updated natural classification of the fungi, with illustrated accounts of species linked to molecular data. The present paper introduces the FoF database to the scientific community and briefly reviews some of the problems associated with classification and identification of the main fungal groups. The structure and use of the database is then explained. We would like to invite all mycologists to contribute to these web pages.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.106 | 0.082 |
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".