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Record W2188205843 · doi:10.21273/jashs.137.5.325

Genetic Variation and Distribution of Pacific Crabapple

2012· article· en· W2188205843 on OpenAlexafffund
Kanin J. Routson, Gayle M. Volk, Christopher M. Richards, S. E. Smith, Gary Paul Nabhan, Victoria Wyllie de Echeverria

Bibliographic record

VenueJournal of the American Society for Horticultural Science · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Victoria
FundersUniversity of AlbertaMuseum of the North, University of AlaskaUniversity of British ColumbiaUniversity of Arizona
KeywordsHabitatRange (aeronautics)BiologyEcologyGenetic diversityIntroduced speciesSpecies distributionGeographyPopulation

Abstract

fetched live from OpenAlex

Pacific crabapple [ Malus fusca (Raf.) C.K. Schneid.] is found in mesic coastal habitats in Pacific northwestern North America. It is one of four apple species native to North America. M. fusca is culturally important to First Nations of the region who value and use the fruit of this species as food, bark and leaves for medicine, and wood for making tools and in construction. However, little is known about either distribution or genetic diversity of this species. To correct this deficiency, we used habitat suitability modeling to map M. fusca habitat types with species occurrence records. The species apparently occupies at least two distinct climate regions: a colder, drier northern region and a warmer, wetter southern region. Total area of modeled habitat encompasses ≈356,780 km 2 of low-lying areas along the Pacific coast. A total of 239 M. fusca individuals sampled from across its native range were genetically compared using six microsatellite markers to assess for possible geographic structuring of genotypes. The primers amplified 50 alleles. Significant isolation by distance was identified across the ≈2600 km (straight line) where samples were distributed. These results may help establish priorities for in situ and ex situ M. fusca conservation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.437

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 studies0.0000.001
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 head0.015
GPT teacher head0.250
Teacher spread0.236 · 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.

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

Citations18
Published2012
Admission routes2
Has abstractyes

Explore more

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