CIGAF—a database and interactive platform for insect-associated trichomycete fungi
Bibliographic record
Abstract
Trichomycete fungi are gut symbionts of arthropods living in aquatic habitats. The lack of a central platform with accessible collection records and associated ecological metadata has limited ecological investigations of trichomycetes. We present CIGAF (short for Collections of Insect Gut-Associated Fungi), a trichomycetes-focused digital database with interactive visualization functions enabled by the R Shiny web application. CIGAF curated 3120 collection records of trichomycetes across the globe, spanning from 1929 to 2022. CIGAF allows the exploration of nearly 100 years of field collection data through the web interface, including primary published data such as insect host information, collection site coordinates, descriptions and date of collection. When possible, specimen records are supplemented with climatic measures at collection sites. As a central platform of field collection records, multiple interactive tools allow users to analyze and plot data at various levels. CIGAF provides a comprehensive resource hub to the research community for further studies in mycology, entomology, symbiosis and biogeography.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.015 |
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".