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Record W2975228822 · doi:10.3114/fuse.2020.05.05

Cones, needles and wood: <i> Micraspis </i> (<i>Micraspidaceae</i>, <i> Micraspidales fam. et ord. nov.</i>) speciation segregates by host plant tissues

2019· article· en· W2975228822 on OpenAlexaff
Luis Quijada, Joey B. Tanney, Е. С. Попов, Peter R. Johnston, Donald H. Pfister

Bibliographic record

VenueFungal Systematics and Evolution · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsBiologyGenusHost (biology)PinaceaeBotanyGenetic algorithmEvolutionary biologyZoologyEcologyPinus <genus>

Abstract

fetched live from OpenAlex

Micraspis acicola was described more than 50 years ago to accommodate a phacidium-like fungus that caused a foliar disease of Picea mariana . After its publication, two more species were added, M. strobilina and M. tetraspora , all of them growing on Pinaceae in the Northern Hemisphere, but each species occupying a unique type of host tissue (needles, cones or wood). Micraspis is considered to be a member of class Leotiomycetes , but was originally placed in Phacidiaceae ( Phacidiales ), later transferred to Helotiaceae ( Helotiales ) and recently returned to Phacidiales but in a different family ( Tympanidaceae ). The genus remains poorly sampled, and hence poorly understood both taxonomically and ecologically. Here, we use morphology, cultures and sequences to provide insights into its systematic position in Leotiomycetes and its ecology. Our results show that the genus should not be included in Tympanidaceae or Phacidiaceae , and support the erection of a new family and order with a unique combination of morphological features supported by molecular data.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score1.000

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)0.0000.000

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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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 designBench or experimental
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

Citations11
Published2019
Admission routes1
Has abstractyes

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