<i>Cerioporus squamosus</i> . [Descriptions of Fungi and Bacteria].
Bibliographic record
Abstract
Abstract A description is provided for Cerioporus squamosus , which causes a white rot of hardwood on living and recently dead broadleaf trees, entering the tree through wounds caused by, for example, lightning, windthrow, soe break and damage by humans and animals. Some information on its associated organisms and substrata, dispersal and transmission, habitats and conservation status is given, along with details of its geographical distribution (Africa (Eritrea, Uganda), Asia (Afghanistan, Armenia, China (Hainan, Heilongjiang, Xinjiang Uighur Autonomous Region), Georgia, India (Himachal Pradesh, Jammu and Kashmir, Uttarakhand, West Bengal), Iran, Japan, Kazakhstan (Aktobe, Almaty, East Kazakhstan, Karagandy, Kostanay, Pavlodar, South Kazakhstan, West Kazakhstan, Zhambyl), Mongolia, Nepal, Pakistan, Russia (Amur Oblast, Chelyabinsk Oblast, Irkutsk Oblast, Kamchatka Krai, Khabarovsk Krai, Khanty-Mansi Autonomous Okrug, Novosibirsk Oblast, Primorsky Krai, Sverdlovsk Oblast, YamaloNenets Autonomous Okrug), South Korea, Taiwan, Tajikistan, Turkey, Turkmenistan, Uzbekistan), Australasia (Australia (Victoria), New Zealand), Central America (Costa Rica), Europe (Albania, Andorra, Austria, Belarus, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Moldova, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Russia (Belgorod Oblast, Bryansk Oblast, Chuvash Republic, Ivanovo Oblast, Kaliningrad Oblast, Kaluga Oblast, Kirov Oblast, Krasnodar Krai, Kursk Oblast, Leningrad Oblast, Moscow Oblast, Nizhny Novgorod Oblast, Orenburg Oblast, Oryol Oblast, Penza Oblast, Perm Krai, Republic of Bashkortostan, Republic of Mordovia, Republic of North Ossetia-Alania, Republic of Tatarstan, Ryazan Oblast, Samara Oblast, Saratov Oblast, Stavropol Krai, Tambov Oblast, Tula Oblast, Tver Oblast, Udmurt Republic, Ulyanovsk Oblast, Vladimir Oblast, Volgograd Oblast, Voronezh Oblast, Yaroslavl Oblast), Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, UK), (North America (Canada (British Columbia, Manitoba, New Brunswick, Nova Scotia, Ontario, Prince Edward Island, Quebec, Saskatchewan, Yukon), Mexico, USA (Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin)), South America (Brazil (São Paulo), Chile, Ecuador, Paraguay))).
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.012 | 0.011 |
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".