The second International Symposium on Fungal Stress: ISFUS
Bibliographic record
Abstract
The topic of 'fungal stress' is central to many important disciplines, including medical mycology, chronobiology, plant and insect pathology, industrial microbiology, material sciences, and astrobiology. The International Symposium on Fungal Stress (ISFUS) brought together researchers, who study fungal stress in a variety of fields. The second ISFUS was held in May 8-11 2017 in Goiania, Goiás, Brazil and hosted by the Instituto de Patologia Tropical e Saúde Pública at the Universidade Federal de Goiás. It was supported by grants from CAPES and FAPEG. Twenty-seven speakers from 15 countries presented their research related to fungal stress biology. The Symposium was divided into seven topics: 1. Fungal biology in extreme environments; 2. Stress mechanisms and responses in fungi: molecular biology, biochemistry, biophysics, and cellular biology; 3. Fungal photobiology in the context of stress; 4. Role of stress in fungal pathogenesis; 5. Fungal stress and bioremediation; 6. Fungal stress in agriculture and forestry; and 7. Fungal stress in industrial applications. This article provides an overview of the science presented and discussed at ISFUS-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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.054 | 0.016 |
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".