<i>Mycosphaerella rubi</i> . [Descriptions of Fungi and Bacteria].
Bibliographic record
Abstract
Abstract A description is provided for Mycosphaerella rubi , which sometimes causes lesions on leaves of Rubus caesius . Some information on its dispersal and transmission and conservation status is given, along with details of its geographical distribution (Africa (Kenya, Libya, Mauritius, South Africa, Zimbabwe)), North America (Canada (British Columbia, New Brunswick, Nova Scotia, Ontario), Mexico, USA (Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Vermont, Virginia, Washington, West Virginia, Wisconsin), South America (Argentina, Chile, Colombia, Uruguay, Venezuela), Asia (Armenia, Azerbaijan, China (Sichuan), Georgia, India, Iran, Iraq, Japan, Kazakhstan, Kyrgyzstan, Russia (Kurgan oblast, Primorskyi krai, Tiumen oblast, Tomsk oblast), South Korea, Taiwan, Turkey, Turkmenistan, Uzbekistan), Australasia (Australia, New Zealand (as exotic)), Caribbean (American Virgin Islands, Puerto Rico), Europe (Albania, Austria, Belarus, Belgium, Bulgaria, Czech Republic, former Czechoslovakia, Estonia, France, Germany, Great Britain, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Macedonia, Malta, Moldova, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Russia (Astrakhan oblast, Kabardino-Balkarskaya Autonomous Republic, Krasnodarskyi krai, Kursk oblast, Leningrad oblast, Moscow oblast, Oryol oblast, Perm oblast, North Ossetia-Alania Autonomous Republic, Samara oblast, Saratov oblast, Stavropolskyi krai, Tambov oblast, Tatarstan, Tula oblast, Tver oblast, Udmurtia, Ufa oblast, Voronezh oblast), Serbia, Spain, Sweden, Switzerland and Ukraine)) and hosts ( Rubus spp.).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".