Neurospora in temperate forests of western North America.
Bibliographic record
Abstract
The fungal genus Neurospora has a distinguished history as a laboratory model in genetics and biochemistry. The most recent milestone in this history has been the sequencing of the genome of the best known species, N. crassa. The hope and promise of a complete genome sequence is a full understanding of the biology of the organism. Full understanding cannot be achieved, however, in the absence of fundamental knowledge of natural history. We report that species of Neurospora, heretofore thought to occur mainly in moist tropical and subtropical regions, are common primary colonizers of trees and shrubs killed by forest fires in western North America, in regions that are often cold and dry. Surveys in 36 forest-fire sites from New Mexico to Alaska yielded more than 500 cultures, 95% of which were the rarely collected N. discreta. Initial characterization of genotypes both within a site and on a single tree showed diversity consistent with sexual reproduction of N. discreta. These discoveries fill important gaps in knowledge of the distribution of members of the genus on both large and small spatial scales and provide the framework for future studies in new regions and microhabitats. The overall result is that population biology and genetics now can be combined, placing the genus Neurospora in a unique position to expand its role in experimental biology as a useful model organism for ecology, population genetics and evolution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".