{"id":"W4381296351","doi":"10.3354/meps14330","title":"Marine bird mass mortality events as an indicator of the impacts of ocean warming","year":2023,"lang":"en","type":"article","venue":"Marine Ecology Progress Series","topic":"Climate variability and models","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Birds Canada","funders":"U.S. Fish and Wildlife Service; National Park Service; Alaska Sea Grant, University of Alaska Fairbanks; National Oceanic and Atmospheric Administration; University of Washington","keywords":"Marine ecosystem; Trophic level; Ecosystem; Climate change; Oceanography; Ecology; Global warming; Environmental science; Geography; Biology; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003999555,0.0002876958,0.0001409777,0.001065334,0.0001717267,0.0004172118,0.0001757506,0.0001816559,0.0008493229],"category_scores_gemma":[0.001035407,0.0001064175,0.000283605,0.0006314203,0.0001355073,0.0002744214,0.0004431509,0.0002868956,0.0001402427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002139408,"about_ca_system_score_gemma":0.000103814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007007163,"about_ca_topic_score_gemma":0.01548684,"domain_scores_codex":[0.9998327,0.0000313307,0.00002721768,0.00004566862,0.00003467602,0.00002837244],"domain_scores_gemma":[0.9986534,0.0001339459,0.0008923694,0.00005737288,0.0001405518,0.0001222164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001707784,0.000005783018,0.9987004,0.000005633314,0.0000241985,0.0000137776,0.00002541485,0.00007681795,0.000236525,0.000004924196,0.00004576056,0.0008438472],"study_design_scores_gemma":[2.734105e-7,0.00001211917,0.9997235,0.000001636263,0.000004902097,0.00001631073,0.00003670989,0.0001150515,0.00003253455,0.000002512487,0.00005383283,5.686904e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981561,0.0001617308,0.0001690248,0.00001497283,0.000006552746,0.000008732126,0.0009063792,0.00001170355,0.0005647334],"genre_scores_gemma":[0.9986308,0.00009830602,0.000166838,0.000009674855,0.00001416661,0.000009968812,0.0008860406,0.000001842703,0.000182387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007007163,"threshold_uncertainty_score":0.0139327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603458932521482,"score_gpt":0.2762974994777347,"score_spread":0.2602629101525198,"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."}}