{"id":"W3179875779","doi":"10.21203/rs.3.rs-627097/v1","title":"Phenological Plasticity and Adaptive Potential of Sugar Maple Populations","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Plant Physiology and Cultivation Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec; Université du Québec en Outaouais; Cégep de Chicoutimi; Université du Québec à Chicoutimi","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China; Ministère des Forêts, de la Faune et des Parcs","keywords":"Phenology; Phenotypic plasticity; Biology; Range (aeronautics); Local adaptation; Maple; Adaptation (eye); Sugar; Annual growth cycle of grapevines; Ecology; Botany; Population","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":[0.0001590975,0.0001586597,0.0001414577,0.000626664,0.0003021597,0.0003639322,0.0001942754,0.00009902885,0.0004598266],"category_scores_gemma":[0.0002792192,0.0000738473,0.0001103966,0.0002913373,0.0001870538,0.0001078086,0.0002395171,0.0001685682,0.00005217823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004682016,"about_ca_system_score_gemma":0.0002952187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02555707,"about_ca_topic_score_gemma":0.07989196,"domain_scores_codex":[0.9999081,0.00001207814,0.00000391323,0.0000320941,0.00001915604,0.00002463304],"domain_scores_gemma":[0.9997411,0.00005015467,0.00005442603,0.00001867387,0.00005162501,0.00008390497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002228678,0.00004918092,0.7352536,0.0000356666,0.00009414982,0.0002095921,0.001012335,0.0004311981,0.2548066,0.00009260562,0.00005490883,0.0077374],"study_design_scores_gemma":[8.803945e-7,0.00001849158,0.999108,6.839135e-7,0.000003567632,0.0000342137,0.0001276507,0.0001528599,0.0004848908,0.00000915362,0.00005754808,0.000001932682],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997944,0.00002524325,0.00004145951,0.000001313205,2.378144e-7,0.000001125082,0.00003945363,0.00000133174,0.00009549889],"genre_scores_gemma":[0.9997354,0.00001524704,0.00005062958,0.000001741369,4.68696e-7,0.000001900396,0.00009786349,0.000001058279,0.00009575461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02555707,"threshold_uncertainty_score":0.0508166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1732691593209155,"score_gpt":0.3570656495863777,"score_spread":0.1837964902654622,"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."}}