{"id":"W3114777199","doi":"10.4095/327811","title":"Temperature and precipitation across Canada","year":2019,"lang":"en","type":"report","venue":"","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Precipitation; Climatology; Environmental science; Physical geography; Geography; Meteorology; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003290407,0.0003132283,0.0003218082,0.002023594,0.002109976,0.001474648,0.0005835718,0.0003194067,0.004262497],"category_scores_gemma":[0.0008375356,0.000212272,0.000505431,0.008699949,0.0003024381,0.0003337035,0.0006331659,0.000589545,0.0006695833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02698714,"about_ca_system_score_gemma":0.05400351,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9988768,"about_ca_topic_score_gemma":0.999414,"domain_scores_codex":[0.999379,0.00002411891,0.0000265427,0.0000795778,0.000287582,0.0002030403],"domain_scores_gemma":[0.9987137,0.00003546794,0.00006161845,0.00002268429,0.0009873935,0.0001790507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007210984,0.0001232239,0.8154069,0.0003626991,0.0004104718,0.0004047343,0.001284222,0.00379305,0.001507151,0.004101656,0.1161685,0.05571621],"study_design_scores_gemma":[0.00001160764,0.000007083727,0.9768374,0.00003018151,0.0000296641,0.00003110512,0.0006414985,0.0004736142,0.0001704884,0.00007546649,0.0216783,0.00001362743],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.619911,0.00624448,0.0006668395,0.003895311,0.0003443135,0.0001713432,0.272953,0.0002447063,0.09556894],"genre_scores_gemma":[0.8678489,0.004464518,0.0009628135,0.000453512,0.00005691817,0.00006563773,0.05432127,0.00006163489,0.07176471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02698714,"threshold_uncertainty_score":0.1958063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0390329215341769,"score_gpt":0.2725851254583029,"score_spread":0.233552203924126,"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."}}