{"id":"W4416876160","doi":"10.1139/facets-2025-0163","title":"Opportunities and challenges for Canada’s mariculture under climate change: a regional and sectoral outlook","year":2025,"lang":"en","type":"article","venue":"FACETS","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Mariculture; Climate change; Production (economics); Investment (military); Indigenous; Adaptation (eye); Global warming; Habitat","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001150531,0.0005531594,0.0002932431,0.0009799117,0.002748993,0.00348304,0.001226136,0.001148543,0.005118421],"category_scores_gemma":[0.001774063,0.0001465318,0.0007836389,0.002325924,0.000862836,0.001064981,0.001532838,0.001014594,0.0003866767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0333487,"about_ca_system_score_gemma":0.09588514,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.985081,"about_ca_topic_score_gemma":0.9936784,"domain_scores_codex":[0.9990566,0.00008644554,0.00001630779,0.00004835343,0.0002258869,0.0005663007],"domain_scores_gemma":[0.9981794,0.00008629316,0.00009461708,0.00003309578,0.0009781201,0.0006285146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006828738,0.0002968919,0.5022979,0.001239716,0.0004568837,0.001719178,0.002981194,0.06884206,0.009989207,0.03207394,0.1229442,0.256476],"study_design_scores_gemma":[0.0000577086,0.0003412686,0.6526919,0.001027298,0.0005021503,0.0004379482,0.03776071,0.06258327,0.003489858,0.0154521,0.2252945,0.0003612933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7612094,0.01958327,0.004368977,0.1017181,0.0005446695,0.0001404144,0.0196677,0.0005400104,0.09222747],"genre_scores_gemma":[0.9745752,0.008534054,0.005409002,0.001629483,0.00004645304,0.00003019775,0.003162213,0.00003894894,0.006574549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0333487,"threshold_uncertainty_score":0.2419629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1158890996141856,"score_gpt":0.2755841486024081,"score_spread":0.1596950489882225,"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."}}