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Record W3011541875 · doi:10.1016/j.ympev.2020.106789

A combined approach of mitochondrial DNA and anchored nuclear phylogenomics sheds light on unrecognized diversity, phylogeny, and historical biogeography of the torrent frogs, genus Amolops (Anura: Ranidae)

2020· article· en· W3011541875 on OpenAlexafffund
Yun‐He Wu, Yan Fang, Bryan L. Stuart, Elizabeth Prendini, Chatmongkon Suwannapoom, Hollis A. Dahn, Baolin Zhang, Hong-Xia Cai, Yong-Biao Xu, Ke Jiang, Hong-Man Chen, Alan R. Lemmon, Emily Moriarty Lemmon, Christopher J. Raxworthy, Nikolai L. Orlov, Robert W. Murphy, Jing Che

Bibliographic record

VenueMolecular Phylogenetics and Evolution · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsRoyal Ontario MuseumUniversity of Toronto
FundersYouth Innovation Promotion AssociationNational Outstanding Youth Science Fund Project of National Natural Science Foundation of ChinaBộ Nông Nghiệp và Phát Triển Nông ThônRussian Foundation for Basic ResearchFlorida State UniversityRome FoundationThailand Research FundChinese Academy of SciencesCalifornia Academy of SciencesNational Natural Science Foundation of ChinaAmerican Museum of Natural HistoryNational Geographic SocietyNatural Sciences and Engineering Research Council of CanadaJohn D. and Catherine T. MacArthur FoundationUniversity of PhayaoNational Science Foundation
KeywordsBiologyParaphylyMonophylyZoologyBiogeographyMolecular phylogeneticsGenusPhylogeneticsEvolutionary biologyEcologyClade

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.162
Teacher spread0.154 · 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

Citations50
Published2020
Admission routes2
Has abstractno

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