Developing an online database of descriptions of ectomycorrhizae
Bibliographic record
Abstract
Ectomycorrhizae are the mutually beneficial symbioses of fungi and fine roots, and are responsible for the uptake of nutrients that support tree growth. Many species of fungi form ectomycorrhizae with conifers; most are Basidiomycetes or Ascomycetes that form large mushrooms found in forests. It is, therefore, important to investigate how forest management practices affect the health, growth patterns, physiological function, and taxonomic diversity of ectomycorrhizae. Identification of ectomycorrhizae is fundamental to such research. To date, several hundred detailed descriptions of ectomycorrhizae have been published in books, journal articles, and on a compact disk database called DEEMY (DEtermination of EctoMYcorrhizae), but hundreds more are unavailable in researchers� private databases. The Database of Descriptions of Ectomycorrhizae (DDE) web site aims to be a comprehensive tool for the identification of ectomycorrhizae by bringing together as many published and unpublished descriptions as possible. A search function, available to all users, has been programmed to act as an electronic synoptic key. The DDE system also allows qualified researchers to add their unpublished descriptions to the database, and to update these descriptions as needed. The DDE database currently contains 338 descriptions; 318 from DEEMY and 20 from A Manual of Concise Descriptions of Ectomycorrhizae (CDE). Entry of descriptions and search profiles is done using a web form with all the characters in the CDE checklist and links to the CDE illustrated glossary.
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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.030 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.079 |
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".