{"id":"W2736940169","doi":"10.1111/gcb.13829","title":"Adaptation strategies to climate change in marine systems","year":2017,"lang":"en","type":"review","venue":"Global Change Biology","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Nippon Foundation","keywords":"Adaptation (eye); Climate change; Climate change adaptation; Environmental resource management; Environmental science; Climatology; Geography; Oceanography; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001343407,0.0009676233,0.0009980344,0.002206125,0.000523688,0.001977734,0.001175517,0.001930624,0.002808839],"category_scores_gemma":[0.002555832,0.0002313262,0.0008118845,0.002826189,0.001444209,0.002269001,0.001270654,0.00113916,0.0006401635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001323419,"about_ca_system_score_gemma":0.002896836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003932859,"about_ca_topic_score_gemma":0.005866459,"domain_scores_codex":[0.999345,0.0002504881,0.00008456212,0.0001066902,0.0001563345,0.00005687078],"domain_scores_gemma":[0.9991048,0.0005641456,0.0001293844,0.00003654243,0.0001261709,0.00003898924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002678739,0.00005165847,0.001026187,0.04129579,0.0003036745,0.0002479571,0.001060271,0.002149524,0.0007441676,0.03181025,0.01501055,0.9062733],"study_design_scores_gemma":[0.000007976149,0.00006283704,0.003683986,0.02495519,0.0002411624,0.0008217228,0.001057007,0.0003040071,0.0004639156,0.01890308,0.9494529,0.0000461399],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005184772,0.9940174,0.0005028726,0.001005727,0.0001586797,0.00001525214,0.00002699679,0.00001122956,0.003743414],"genre_scores_gemma":[0.005769732,0.9927517,0.0005434823,0.0003096657,0.00009784701,0.00001746621,0.0000273318,0.000003007551,0.0004796779],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003932859,"threshold_uncertainty_score":0.009602129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2875085411351803,"score_gpt":0.423831188516567,"score_spread":0.1363226473813867,"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."}}