{"id":"W2126426853","doi":"10.4141/p00-030","title":"Canada’s plant hardiness zones revisited using modern climate interpolation techniques","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Plant Science","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Agriculture","keywords":"Hardiness (plants); Elevation (ballistics); Latitude; Physical geography; Geography; Longitude; Climate change; Environmental science; Bivariate analysis; Multivariate interpolation; Digital elevation model; Climatology; Statistics; Mathematics; Geology; Remote sensing; Ecology; Geodesy; Biology; Agronomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001412648,0.0004162738,0.0003853444,0.002647718,0.001768356,0.002087997,0.001123422,0.0002027635,0.002235798],"category_scores_gemma":[0.005959512,0.0002429556,0.00069513,0.009866379,0.0005866239,0.0005180775,0.001127494,0.0008488202,0.0001539682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01400132,"about_ca_system_score_gemma":0.01773857,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9801409,"about_ca_topic_score_gemma":0.9855621,"domain_scores_codex":[0.9991527,0.0001271897,0.00003690175,0.0001583991,0.0003808685,0.0001439131],"domain_scores_gemma":[0.9979901,0.0005198717,0.0001948484,0.0002866455,0.0009091643,0.00009934064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003325075,0.00006210292,0.300443,0.0004090099,0.0004020002,0.0006782519,0.005701383,0.1198915,0.003057861,0.0542406,0.01823157,0.4965502],"study_design_scores_gemma":[0.00005363732,0.00004162815,0.6170017,0.0002956708,0.0001950258,0.0002650101,0.003498929,0.2346174,0.003092856,0.01451614,0.1262456,0.0001763633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7790785,0.004676283,0.1377436,0.002445597,0.0002905829,0.0001868855,0.01265228,0.002024183,0.06090215],"genre_scores_gemma":[0.9117109,0.00089633,0.07794356,0.00009929254,0.00002966555,0.00004267913,0.003088909,0.0001981882,0.005990497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01985914,"threshold_uncertainty_score":0.1015872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04099203087261512,"score_gpt":0.2349449426512528,"score_spread":0.1939529117786377,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}