{"id":"W6906604495","doi":"10.17616/r3nd2k","title":"Canadian Climate Data and Scenarios","year":2016,"lang":"en","type":"other","venue":"Registry of Research Repositories","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Adaptation (eye); Decision support system; Climate change adaptation; Interface (matter); Climate model","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.00222159,0.001631703,0.0008236592,0.01270417,0.004052848,0.00538693,0.002547827,0.0009333418,0.0812225],"category_scores_gemma":[0.01555666,0.0007983677,0.001431848,0.0295033,0.0005473514,0.002093751,0.001992179,0.001895963,0.02146727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05068501,"about_ca_system_score_gemma":0.1128203,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9891627,"about_ca_topic_score_gemma":0.98987,"domain_scores_codex":[0.9957071,0.0001831448,0.0002448324,0.000334941,0.003040145,0.0004897359],"domain_scores_gemma":[0.9860686,0.0004705882,0.0002901416,0.001020769,0.01133797,0.0008119122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005893052,0.00001921928,0.002045197,0.0003062605,0.0000358359,0.0000489216,0.0001763918,0.001918689,0.000149915,0.01860533,0.9544011,0.02223424],"study_design_scores_gemma":[0.00002055611,0.000002600409,0.004887745,0.0001358467,0.00001733036,0.00001923653,0.0001500435,0.0007754817,0.0002659373,0.0021319,0.9915467,0.00004666115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0009348067,0.0003563249,0.001079659,0.000756406,0.0001791108,0.000121292,0.8800389,0.001260294,0.1152733],"genre_scores_gemma":[0.01405365,0.002213136,0.007693595,0.0003384794,0.00004606939,0.0003380947,0.925833,0.0008292201,0.04865465],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0812225,"threshold_uncertainty_score":0.3677472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04544914860868395,"score_gpt":0.3367043524547888,"score_spread":0.2912552038461049,"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."}}