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Record W2090570997 · doi:10.1300/j301v02n01_06

Revised International Registry of Cultivars and Germplasm of the Genus<i>Amelanchier</i>

2003· article· en· W2090570997 on OpenAlexaffabout
A. M. Zatylny, R. G. St-Pierre

Bibliographic record

VenueSmall Fruits Review · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCultivarGermplasmBiologyOrnamental plantGenusGeographyBotanyHorticulture

Abstract

fetched live from OpenAlex

An updated International Registry of the genus Amelanchier, consisting of 32 ornamental cultivars and 25 cultivars grown for fruit, was created on the basis of published information, unpublished research data, and observations made by originators or their successors. Additionally, in 1997 a survey of the location and availability of Amelanchier germplasm was sent to 60 botanical gardens and arboreta across Canada and throughout the central and northern United States. Thirty-three replies were received of which 31 of the gardens or arboreta had Amelanchier germplasm. The collection of Amelanchier at the University of Saskatchewan was included in the survey results. The survey indicated that various Amelanchier species and cultivars are widely distributed. A total of 25 different species, subspecies or varieties, 8 different hybrids, and 42 different cultivars were reported as being held in the collections surveyed. This study comprises the most recent, comprehensive and quantitatively characterised list of Amelanchier cultivars to date. This information will be beneficial to the nursery industry in terms of cultivar characterisation, the exchange of plant material, and the development and distribution of new Amelanchier cultivars.

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)0.005
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0110.010
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.025
GPT teacher head0.230
Teacher spread0.206 · 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

Citations14
Published2003
Admission routes2
Has abstractyes

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