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Record W4415382863 · doi:10.56367/oag-048-11711

Clones for viticulture in Canada: National clonal selection program

2025· article· en· W4415382863 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOpen Access Government · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsBrock University
Fundersnot available
KeywordsVineViticultureClonal selectionCuttingSelection (genetic algorithm)Vitis vinifera

Abstract

fetched live from OpenAlex

Clones for viticulture in Canada: National clonal selection program Jim Willwerth from CCOVI at Brock University highlights the importance of clonal propagation in grapevine cultivation, as new vines are grown from cuttings of a ‘mother vine’ to preserve desirable traits. He also advocates for a national clonal selection program to assess new clones for Canada’s cool climate. Commercial grapevine propagation is primarily performed through vegetative propagation, resulting in clonal propagation. This typically involves taking a cutting from a mother vine and creating conditions for it to establish roots and grow as a new vine. The individual vine or group of vines propagated from this single organism (the mother vine) is called a ‘clone’. This ensures that new vines remain ‘true to type’ where the variety with desirable attributes is retained and then planted in vineyards.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.620

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 communication0.0010.001
Open science0.0010.000
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 head0.062
GPT teacher head0.390
Teacher spread0.329 · 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