{"id":"W2910111203","doi":"10.1111/1365-2656.12932","title":"Salmonid species diversity predicts salmon consumption by terrestrial wildlife","year":2019,"lang":"en","type":"article","venue":"Journal of Animal Ecology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Alberta; Raincoast Conservation Foundation; Traffic Injury Research Foundation; Tula Foundation; Vancouver Coastal Health; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Hakai Institute; Wilburforce Foundation","keywords":"Interspecific competition; Grizzly Bears; Ecology; Oncorhynchus; Ursus; Competition (biology); Productivity; Biomass (ecology); Abundance (ecology); Sympatric speciation; Intraspecific competition; Biology; Wildlife; Geography; Population; Fishery; Fish <Actinopterygii>; Demography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003274244,0.0001709733,0.00011084,0.0005103518,0.0003367713,0.0005712218,0.0001745312,0.000274794,0.003441306],"category_scores_gemma":[0.001183359,0.0002130075,0.0002077492,0.0004953407,0.0002992621,0.0002085488,0.0003045166,0.0002491463,0.0005515505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004941209,"about_ca_system_score_gemma":0.0004843451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1428116,"about_ca_topic_score_gemma":0.3340738,"domain_scores_codex":[0.9999148,0.00001818644,0.00000633538,0.0000235031,0.00001231495,0.00002497406],"domain_scores_gemma":[0.9992825,0.000156277,0.0002201173,0.00003239925,0.00008919481,0.000219394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001391564,0.00000627293,0.9989117,0.00000200089,0.0000142148,0.000007316376,0.00002878352,0.0001245779,0.0001861958,0.00001112194,0.00006220153,0.0006316615],"study_design_scores_gemma":[6.854008e-7,0.000005735038,0.9993777,0.000002711565,0.000004869506,0.000008838702,0.0000921796,0.0004261679,0.00001321573,0.0000179985,0.00004901493,8.665047e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991546,0.00005689292,0.00005939229,0.00002728716,7.879779e-7,0.000001584025,0.0001627387,0.000003733754,0.0005329573],"genre_scores_gemma":[0.9993529,0.00004623276,0.00004846099,0.000007962297,0.000001415748,0.000001907679,0.0002313374,0.000002137539,0.0003075943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1428116,"threshold_uncertainty_score":0.2839606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509510232208748,"score_gpt":0.2182561122324,"score_spread":0.2031610099103126,"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."}}