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Record W3035752583 · doi:10.1080/15538362.2020.1774471

Wintering Index and Yield Traits for Early, Mid, and Late Season Strawberry for Colder Climates

2020· article· en· W3035752583 on OpenAlex
Sajjad Ali Rao, Anthony Scott Mintenko, Lord Abbey, Poonam Singh

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

VenueInternational Journal of Fruit Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsDalhousie UniversityAgriculture Food and Rural DevelopmentAssiniboine Community College
Fundersnot available
KeywordsCultivarHardiness (plants)Temperate climateGrowing seasonBiologyYield (engineering)Perennial plantAgronomyHorticultureSnowFragariaGeographyBotanyMeteorology

Abstract

fetched live from OpenAlex

In temperate climatic regions where severe winter conditions persist, the winter hardiness and fruit yield of strawberry cultivars vary greatly in perennial production systems. A 4-year study was carried out to investigate the wintering ability of different June-bearing strawberry cultivars in the cold semi-arid continental climate of Manitoba between 2015 and 2018. The wintering index and yield traits of early, mid, and late season strawberry cultivars were evaluated. Six different cultivars tested in each year. ‘Wendy,’ ‘Kent’, and ‘Cabot’ were common in each year. Mid-season cultivar ‘Kent’ and ‘Mira’ yielded significantly (p< .05) higher with greater wintering index compared to early and late season cultivars within each trial and across 4 years. Low winter temperatures with less snow on grounds establish pronounced effect on early season cultivars wintering index. A significant variation for temperatures was recorded for the months within and between years.

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 score0.928
Threshold uncertainty score0.229

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 head0.073
GPT teacher head0.310
Teacher spread0.237 · 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