{"id":"W4385954714","doi":"10.3389/fmars.2023.1168573","title":"Canada and ocean climate adaptation: tracking law and policy responses, charting future directions","year":2023,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Climate change; Indigenous; Adaptation (eye); Political science; Action plan; Corporate governance; Environmental resource management; Government (linguistics); Climate change adaptation; Environmental planning; Geography; Public administration; Business; Ecology; Economics; Management","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":[0.03025743,0.0007911149,0.0008984387,0.00869534,0.01878894,0.02470786,0.004926822,0.006058429,0.00610547],"category_scores_gemma":[0.04864125,0.0006880685,0.0009290481,0.01784648,0.01418902,0.008901194,0.006092614,0.008469215,0.0006173133],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.261909,"about_ca_system_score_gemma":0.5979791,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9913847,"about_ca_topic_score_gemma":0.9934276,"domain_scores_codex":[0.9634304,0.004891044,0.001422346,0.002203318,0.01940758,0.008645378],"domain_scores_gemma":[0.9268433,0.01007069,0.003432641,0.001848431,0.0485169,0.009288066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006395729,0.0001754856,0.04158875,0.001483788,0.0000764359,0.0004463091,0.0110308,0.004595499,0.0007669896,0.3598635,0.3644351,0.2154734],"study_design_scores_gemma":[0.0000244497,0.00004602428,0.04910954,0.002668784,0.00005654219,0.00007404302,0.02898929,0.003074966,0.0006786122,0.03028349,0.8847638,0.0002302799],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02451906,0.04369195,0.005052847,0.7564634,0.002720942,0.0005786982,0.003172396,0.000572637,0.1632281],"genre_scores_gemma":[0.5414575,0.1096355,0.04638695,0.2184577,0.001224613,0.0009665174,0.005296723,0.0004404233,0.07613409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.261909,"threshold_uncertainty_score":0.8560809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697707808646304,"score_gpt":0.2940758173828683,"score_spread":0.2770987392964052,"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."}}