{"id":"W3006296777","doi":"10.1111/gcb.14974","title":"Projecting global mariculture diversity under climate change","year":2020,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mariculture; Species richness; Climate change; Aquaculture; Geography; Ecology; Fishery; Biology; Fish <Actinopterygii>","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":[0.000558349,0.0005876102,0.0002745416,0.000664942,0.000310769,0.0007839459,0.000531815,0.000763265,0.001308874],"category_scores_gemma":[0.001240642,0.0002275639,0.001031441,0.001242736,0.0002496787,0.001153136,0.000893945,0.0006268131,0.0002791526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166136,"about_ca_system_score_gemma":0.001183239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06150831,"about_ca_topic_score_gemma":0.0351389,"domain_scores_codex":[0.999858,0.00003986802,0.000007118872,0.00003527525,0.00002412237,0.00003564018],"domain_scores_gemma":[0.9996986,0.00006471032,0.00005441915,0.00003388611,0.00008560225,0.00006277827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001487576,0.00005085006,0.1414262,0.0001108487,0.0002749885,0.0001877644,0.0001297967,0.8342429,0.002635328,0.002504234,0.002293923,0.0159944],"study_design_scores_gemma":[0.00005578706,0.0001219163,0.1531016,0.00006388354,0.0002152918,0.0001052921,0.0004655923,0.8308349,0.001824378,0.00603799,0.00707688,0.00009650323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791124,0.0004422142,0.008403433,0.0009701085,0.00005991235,0.00002551715,0.006160578,0.0001759339,0.00464998],"genre_scores_gemma":[0.9915202,0.0004880009,0.003712354,0.000115409,0.00001549195,0.00004432897,0.003711469,0.00002793136,0.0003648555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06150831,"threshold_uncertainty_score":0.1223006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1182550359303578,"score_gpt":0.3032547003038515,"score_spread":0.1849996643734937,"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."}}