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Record W4200445874 · doi:10.1079/dfb/20210499498

<i>Fomitopsis betulina</i> . [Descriptions of Fungi and Bacteria].

2021· article· en· W4200445874 on OpenAlexaboutno aff
D. W. Minter, G. S. Soliman

Bibliographic record

VenueDescriptions of Fungi and Bacteria · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsGeographySamaraRussian federationEnvironmental protectionForestryEcologyBiology

Abstract

fetched live from OpenAlex

Abstract A description is provided for Fomitopsis betulina . Sporophores of this fungus are found on both living and dead trees, where the fungus causes a brown-rot decay of heartwood, eventually reducing the substratum to a red-brown friable mass. Some information on its associated organisms and substrata, dispersal and transmission, habitats and conservation status is given, along with details of its geographical distribution (Asia (China (Gansu, Heilongjiang, Jilin, Nei Mongol Autonomous Region, Shaanxi, Sichuan, Xinjiang Autonomous Region, Yunnan), India (Meghalaya, Uttarakhand), Iran, Japan, Kazakhstan (Akmola, East Kazakhstan, Kostanay, North Kazakhstan), Nepal, Russia (Altai Krai, Altai Republic, Amur Oblast, Chelyabinsk Oblast, Irkutsk Oblast, Kamchatka Krai, Khabarovsk Krai, Khanty-Mansi Autonomous Okrug, Krasnoyarsk Krai, Novosibirsk Oblast, Omsk Oblast, Primorsky Krai, Sakha Republic, Sakhalin Oblast, Sverdlovsk Oblast, Tomsk Oblast, Tyumen Oblast, Yamalo-Nenets Autonomous Okrug, Zabaykalsky Krai), South Korea, Uzbekistan), Central America (Belize, Panama), Europe (Åland Islands, Andorra, Austria, Belarus, Belgium, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Isle of Man, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Russia (Bryansk Oblast, Chuvash Republic, Ivanovo Oblast, Kaliningrad Oblast, Kaluga Oblast, Kirov Oblast, Komi Republic, Kostroma Oblast, Krasnodar Krai, Kursk Oblast, Leningrad Oblast, Mari El Republic, Moscow Oblast, Murmansk Oblast, Nizhny Novgorod Oblast, Orenburg Oblast, Perm Krai, Pskov Oblast, Republic of Bashkortostan, Republic of Dagestan, Republic of Karelia, Republic of Mordovia, Republic of Tatarstan, Ryazan Oblast, Samara Oblast, Saratov Oblast, Smolensk Oblast, Tula Oblast, Tver Oblast, Udmurt Republic, Vladimir Oblast, Yaroslavl Oblast), Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, UK), North America (Canada (Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Northwest Territories, Nova Scotia, Ontario, Prince Edward Island, Quebec, Yukon Territory), USA (Alabama, Alaska, Arkansas, California, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Montana, Nebraska, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Vermont, Virginia, Washington, West Virginia, Wisconsin)), South America (Argentina, Colombia)).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.006

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.

Opus teacher head0.015
GPT teacher head0.200
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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