MétaCan
Menu
Back to cohort
Record W4236460116 · doi:10.1079/dmpd/20163365143

<i>Aphanomyces euteiches</i> . [Distribution map].

2016· article· en· W4236460116 on OpenAlexaboutno aff
CABI, EPPO

Bibliographic record

VenueDistribution Maps of Plant Diseases · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyChinaDistribution (mathematics)Archaeology

Abstract

fetched live from OpenAlex

Abstract A new distribution map is provided for Aphanomyces euteiches Drechsler. Oomycetes: Saprolegniales: Leptolegniaceae. Hosts: many legumes, but especially pea ( Pisum sativum ), bean ( Phaseolus vulgaris ) and lucerne ( Medicago sativa ). Information is given on the geographical distribution in Europe (Czech Republic, Denmark, Finland, France, Italy, Netherlands, Norway, Poland, Russia, Spain, Sweden, UK, England and Wales, Scotland and Ukraine), Asia (China, Gansu, India, Madhya Pradesh, Japan and Nepal), North America (Canada, Alberta, Manitoba, Ontario, Quebec, Saskatchewan, Mexico, USA, Alabama, California, Colorado, Connecticut, Delaware, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Montana, Nebraska, New Jersey, New York, North Carolina, North Dakota, Oregon, Pennsylvania, South Dakota, Utah, Virginia, Washington and Wisconsin), Central America and Caribbean (Jamaica) and Oceania (Australia, New South Wales, Queensland, South Australia, Tasmania, Victoria and New Zealand).

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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.128
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1280.056

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 head0.011
GPT teacher head0.196
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
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueDistribution Maps of Plant DiseasesSame topicPlant Pathogens and ResistanceFrench-language works237,207