<i>Cryptomyces maximus</i> . [Descriptions of Fungi and Bacteria].
Bibliographic record
Abstract
Abstract A description is provided for Cryptomyces maximus . Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. DISEASE: Cryptomyces maximus grows on dead portions of otherwise living willow twigs and branches, and is clearly at least partly responsible for killing them. Even some of the earliest literature noted how diseased willows infected by this fungus can appear (GREVILLE, 1826). At a site in SW Wales the author noted that the only trees infected were small scrubby bushes in a ditch next to an area with several horses. The horses had access to the bushes, and there was evidence that the trees had received significant damage from attempted grazing by the horses. In Britain, the fungus has been recorded producing ascospores in May. HOSTS: Salix caprea (living twig, living wood), S. elaeagnos (twig), S. fragilis (twig), S. herbacea (twig), S . lanceolata (twig), S. myrsinifolia (twig), S. pellita (twig), S . pentandra (twig), S. phylicifolia (twig), S. viminalis (twig), Salix sp. (attached twig). GEOGRAPHICAL DISTRIBUTION: NORTH AMERICA: Canada (Saskatchewan), USA (Colorado, Utah). EUROPE: Denmark, Germany, Great Britain, Iceland, Ireland, Norway, Russia (Arkhangel, Kursk, Leningrad), Sweden, Ukraine. TRANSMISSION: Not known. Presumably by air-borne ascospores released in humid conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".