{"id":"W2574793527","doi":"10.1038/s41559-016-0060","title":"Climate change ecology: Hot under the collar","year":2017,"lang":"en","type":"article","venue":"Nature Ecology & Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Ecology; Collar; Climate change; Biology; Engineering","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":[0.001899863,0.0003399113,0.0005300733,0.0007678914,0.003226198,0.004829614,0.0005251574,0.001259216,0.01627425],"category_scores_gemma":[0.003400875,0.000223344,0.0002657061,0.001100729,0.003902072,0.003685791,0.003659726,0.00187415,0.001740037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091434,"about_ca_system_score_gemma":0.0008208346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006250819,"about_ca_topic_score_gemma":0.01916704,"domain_scores_codex":[0.9990396,0.0003171079,0.00002054494,0.0001512591,0.0001633928,0.0003080227],"domain_scores_gemma":[0.9980968,0.0003410433,0.0002432626,0.0002998763,0.0003784947,0.0006404956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005155821,0.00008764096,0.2279244,0.0002503998,0.0003791519,0.002100497,0.01321586,0.00133748,0.004485019,0.217114,0.2145441,0.3180458],"study_design_scores_gemma":[0.00004651936,0.0001534583,0.3106261,0.0003098173,0.000120038,0.001207498,0.02879192,0.0009556885,0.0007644031,0.2026711,0.4542364,0.0001170117],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4056297,0.018523,0.005620967,0.3517953,0.007236293,0.00002521438,0.0007380322,0.0002322164,0.2101993],"genre_scores_gemma":[0.9630001,0.00444995,0.0006127917,0.01641339,0.002381386,0.000009471873,0.0001478834,0.0001119853,0.01287307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01627425,"threshold_uncertainty_score":0.05444276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02083706806440942,"score_gpt":0.2735082406809815,"score_spread":0.252671172616572,"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."}}