{"id":"W3082468995","doi":"10.1111/gcb.15327","title":"Growing‐season frost is a better predictor of tree growth than mean annual temperature in boreal mixedwood forest plantations","year":2020,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Center for Northern Studies; Université du Québec à Montréal; Université du Québec en Abitibi-Témiscamingue","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Frost (temperature); Taiga; Boreal; Growing season; Black spruce; Temperate climate; Ecotone; Alpine climate; Environmental science; Picea abies; Picea engelmannii; Agronomy; Biology; Ecology; Geography; Pinus contorta; Shrub","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003745893,0.0002875534,0.0001797585,0.0002753744,0.0003458175,0.0003968709,0.0001986649,0.0001435629,0.0003348556],"category_scores_gemma":[0.000458544,0.0001260991,0.0001466249,0.0001644849,0.0001966625,0.0001648726,0.0001542579,0.0002029461,0.00007395202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005202293,"about_ca_system_score_gemma":0.0003176296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1154837,"about_ca_topic_score_gemma":0.4096224,"domain_scores_codex":[0.999856,0.00002338448,0.000008929644,0.00005016025,0.00002862412,0.00003284546],"domain_scores_gemma":[0.9994405,0.00007524226,0.000154403,0.00003281434,0.00007517232,0.0002218489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001027509,0.00004240915,0.9921814,0.000005960079,0.00002663001,0.00002407384,0.00009192511,0.000109739,0.005842297,0.000006408139,0.00004915871,0.001517261],"study_design_scores_gemma":[5.990951e-7,0.00001292549,0.9998009,4.360301e-7,0.000002011647,0.00001163604,0.00002147146,0.00007009424,0.00005500716,0.000001552894,0.00002290635,6.593277e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999803,0.00003213569,0.00003412159,0.000004041239,0.000001086772,0.000001216667,0.00004260068,0.000002498874,0.00007922385],"genre_scores_gemma":[0.9996389,0.00001710148,0.0001023381,0.000005967536,0.000001187157,0.000001399436,0.0001347923,0.000001694548,0.00009651922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1154837,"threshold_uncertainty_score":0.229623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02476212636173072,"score_gpt":0.2424813279416665,"score_spread":0.2177192015799358,"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."}}