{"id":"W3198289004","doi":"10.1111/ele.13866","title":"Predicting how climate change threatens the prey base of Arctic marine predators","year":2021,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Government of Canada; University of British Columbia; Fisheries and Oceans Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Predation; Arctic; Climate change; Bay; Environmental science; Ecology; Abundance (ecology); Range (aeronautics); Temperate climate; Fishery; Biology; Oceanography","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":[0.0004159727,0.0004306193,0.000202317,0.0003480633,0.0002820758,0.0008433866,0.000386875,0.0007624744,0.001403206],"category_scores_gemma":[0.000892179,0.0002878906,0.0004583808,0.0002809576,0.0002600919,0.0007794987,0.0004557126,0.0003903457,0.0001586662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009683809,"about_ca_system_score_gemma":0.0005907551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06598211,"about_ca_topic_score_gemma":0.06104936,"domain_scores_codex":[0.9999278,0.00002876851,0.000003028723,0.00001539543,0.000006070442,0.00001903578],"domain_scores_gemma":[0.9997525,0.0001146801,0.00003833863,0.00001008926,0.00003682748,0.00004756022],"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":[0.00008063913,0.00003057326,0.1295646,0.00004641282,0.0001092094,0.0001136472,0.00004928135,0.8627498,0.001526584,0.001215608,0.0006221378,0.0038914],"study_design_scores_gemma":[0.00002853757,0.000130836,0.07165487,0.0000339162,0.0001037269,0.00006219611,0.0003106434,0.9221053,0.0006677742,0.003281462,0.001584977,0.00003588543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931854,0.0003083758,0.002246005,0.0004447683,0.00001996017,0.000005420066,0.0004774482,0.00002448087,0.003287999],"genre_scores_gemma":[0.9980273,0.0002617579,0.001008696,0.00005006382,0.000008887541,0.000006263737,0.0002502965,0.000007667731,0.0003790004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06598211,"threshold_uncertainty_score":0.1311961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02139089488210329,"score_gpt":0.2159614708425608,"score_spread":0.1945705759604575,"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."}}