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Record W4289846251 · doi:10.1079/dfb/20173377622

<i>Cercospora althaeina</i> .

2018· article· en· W4289846251 on OpenAlexaboutno aff
Т. В. Андріанова, D. W. Minter

Bibliographic record

VenueDescriptions of Fungi and Bacteria · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyChinaEnvironmental protectionForestryArchaeology

Abstract

fetched live from OpenAlex

Abstract A description is provided for Cercospora althaeina , which causes brown angular leaf spots on species of Althaea and other members of the Malvaceae. Some information on its associated organisms and substrata, habitats, dispersal and transmission, and conservation status is given, along with details of its geographical distribution (Africa (Kenya, Malawi, Zambia, Zimbabwe), Central America (Guatemala), North America (Canada (Manitoba, Ontario), Mexico, USA (Alabama, Connecticut, Delaware, Florida, Georgia, Illinois, Indiana, Iowa, Kansas, Louisiana, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Nebraska, New Jersey, New York, North Carolina, Pennsylvania, Ohio, Oklahoma, South Carolina, South Dakota, Texas, Virginia, Washington DC, West Virginia, Wisconsin)), South America (Argentina, Brazil, Colombia, Venezuela, Asia, Armenia, Azerbaijan, Bangladesh, China (Guangdong), Burma, Georgia, India (Assam, Bihar, Chhattisgarh, Karnataka, Jammu and Kashmir, Maharashtra, Uttarakhand, West Bengal), Iran, Japan, Kazakhstan (formerly Almaty oblast, East Kazakhstan oblast, former Kostanai oblast, former North Kazakhstan oblast, Zhambyl oblast), Kyrgyztan, Malaysia, Pakistan, Russia (Khabarovsk krai, Primorsky krai, South Korea, Taiwan, Tajikistan, Thailand, Turkey)), Atlantic Ocean (Bermuda), Australasia (Australia (New South Wales), New Zealand), Caribbean (Cuba, Jamaica), Europe (Belarus, Bulgaria, France, Germany, Lithuania, Moldova, Netherlands, Norway, Poland, Romania, Russia (Astrakhan oblast, Krasnodar Krai, Kursk oblast, Lipetsk oblast, Nizhny Novrogod oblast, Orel oblast, Penza oblast, Republic of Kabardino Balkaria, Ryazan oblast, Stavropol krai, Tambov oblast, Volgograd oblast, Voronezh oblast), Sweden, Switzerland, Ukraine, UK), Indian Ocean (Mauritius), Pacific Ocean (American Samoa, USA (Hawaii))).

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.024
GPT teacher head0.203
Teacher spread0.179 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

Explore more

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