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Record W3010021863 · doi:10.1051/ocl/2020004

Gene banks for wild and cultivated sunflower genetic resources

2020· article· en· W3010021863 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOCL · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSunflower and Safflower Cultivation
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsSunflowerGermplasmHelianthus annuusEcotypeBiologyGene poolCropGenetic resourcesHelianthusGenetic diversityBotanyAgronomyBiotechnologyPopulation

Abstract

fetched live from OpenAlex

Modern breeding of sunflower ( Helianthus annuus L .), which started 100 years ago, increased the number and the diversity of cultivated forms. In addition, for more than 50 years, wild sunflower and other Helianthus species have been collected in North America where they all originated. Collections of both cultivated and wild forms are maintained in gene banks in many countries where sunflower is an important crop, with some specificity according to the availability of germplasm and to local research and breeding programmes. Cultivated material includes land races, open pollinated varieties, synthetics and inbred lines. The majority of wild accessions are ecotypes of wild Helianthus annuus , but also 52 other species of Helianthus and a few related genera. The activities of three gene banks, in USA, France and Serbia, are described in detail, supplemented by data from seven other countries. Past and future uses of the genetic resources for environmental adaptation and breeding are discussed in relation to genomic and improved phenotypic knowledge of the cultivated and wild accessions available in the gene banks.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.175

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 head0.025
GPT teacher head0.208
Teacher spread0.184 · 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