{"id":"W7009655141","doi":"","title":"Évaluation des impacts des changements climatiques sur l'apport en eau des Grands Lacs d'Amérique du Nord à l'aide de modèles régionaux du climat","year":2019,"lang":"fr","type":"other","venue":"Corpus Université Laval (Université Laval)","topic":"Phytoplasmas and Hemiptera pathogens","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministère de l'Économie, de la Science et de l'Innovation - Québec; Compute Canada; Université du Québec à Montréal; Environment and Climate Change Canada; Mitacs; McGill University","keywords":"Population; Western europe; Water table; Water consumption","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008966844,0.001060467,0.00107353,0.0003376867,0.001534994,0.0002218973,0.001220956,0.0009754076,0.001514618],"category_scores_gemma":[0.0001344279,0.0007535871,0.0007277472,0.0009262157,0.0007267525,0.0009932333,0.0007732073,0.0005113548,0.0002453983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002385302,"about_ca_system_score_gemma":0.0003122607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01280307,"about_ca_topic_score_gemma":0.1961839,"domain_scores_codex":[0.9955612,0.0006468259,0.0005126983,0.001139489,0.0006847961,0.001454993],"domain_scores_gemma":[0.9971899,0.0004697695,0.0006735049,0.0003483399,0.0006085957,0.0007098334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005802946,0.0005611622,0.7583488,0.0006802696,0.0004921633,0.0006206792,0.0340051,0.0002082639,0.07877403,0.003449709,0.002548256,0.1197313],"study_design_scores_gemma":[0.002994789,0.001724974,0.8050599,0.002008147,0.001081065,0.0003325593,0.0106173,0.002400737,0.01310972,0.002764854,0.1556384,0.002267592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8984826,0.002368963,0.0003275112,0.001122921,0.0004498111,0.0008978739,0.0005303866,0.0002685762,0.09555132],"genre_scores_gemma":[0.6370651,0.09667223,0.004128977,0.0003511517,0.001204625,0.00001279912,0.001020167,0.000117906,0.2594271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2614176,"threshold_uncertainty_score":0.9997649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02882406081537267,"score_gpt":0.2041024367546846,"score_spread":0.1752783759393119,"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."}}