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Xylariales: First results of mycological exploration in the Sangay and Llanganates National Park, Ecuador

2018· preprint· en· W4251501283 on OpenAlexfundno aff
María Fernanda Guevara, Paula Salazar, Bence Mátyás, María-Eugenia Ordoñez

Bibliographic record

VenueF1000Research · 2018
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersSecretaría de Educación Superior, Ciencia, Tecnología e InnovaciónCentre québécois sur les matériaux fonctionnels
KeywordsPhylogenetic treeBiologyRibosomal DNAGenusZoologyEvolutionary biologyNational parkIdentification (biology)BotanyEcologyGeneticsGene

Abstract

fetched live from OpenAlex

In the present study fungi collections were sampled in the Sangay (SP) and Llanganates (LP) National Parks, from which sequences of the regions of the internal transcribable spacer (ITS1-5.8S-ITS2) of the ribosomal DNA were obtained (RDNA). The taxonomic identification of fungi of the order Xylariales was achieved with the bioinformatic tools, to further study the phylogenetic relationships among the collected individuals and thus contribute with base information on their biological diversity, necessary to design and implement measures for the conservation of fungi. All records belong to the genus Xylaria, of these eight belong to PL and two to SP. A record was not identified at the species level, suggesting that it could be a new species. A phylogenetic tree of Maximum Likelihood was built.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.330
Teacher spread0.258 · 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 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

Citations3
Published2018
Admission routes1
Has abstractyes

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