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Record W2144873571 · doi:10.1093/biosci/biu016

Change and Evolution in the Plant Hardiness Zones of Canada

2014· article· en· W2144873571 on OpenAlexaffabout
Daniel W. McKenney, John Pedlar, Kevin Lawrence, Pia Papadopol, K Campbell, Michael F. Hutchinson

Bibliographic record

VenueBioScience · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsHardiness (plants)GeographyAgricultureProductivityClimate changePhysical geographyEcologyBiologyAgronomyArchaeology

Abstract

fetched live from OpenAlex

We present 50-year updates for two plant hardiness models (maps), developed originally by Agriculture Canada and the US Department of Agriculture (USDA), that are widely used for plant selection decisions in Canada. The updated maps show clear northward shifts in hardiness zones across western Canada. Shifts are less dramatic in southeastern Canada, with modest increases in zone values associated with the Canadian map but modest declines associated with the USDA approach. Species-specific climate envelope models are an alternative to generalized hardiness zones. We generated climate envelopes for 62 northern tree species over the same 50-year interval and found an average northward shift of 57 kilometers. These changes signal an increase in the productivity and diversity of plants that can be grown in Canada. However, late spring frosts and other factors discussed herein may limit the extent to which this potential is realized.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.167
Teacher spread0.155 · 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 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

Citations45
Published2014
Admission routes2
Has abstractyes

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