{"id":"W4396906446","doi":"10.1016/j.tree.2024.03.009","title":"Forecasting species’ responses to climate change using space-for-time substitution","year":2024,"lang":"en","type":"review","venue":"Trends in Ecology & Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of Ottawa","funders":"","keywords":"Context (archaeology); Climate change; Threatened species; Ecology; Range (aeronautics); Species distribution; Environmental resource management; Geography; Biology; Environmental science; Habitat; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007489506,0.0004662741,0.0009542893,0.0006873108,0.0002451059,0.00005168881,0.0002865061,0.0005063284,0.009867379],"category_scores_gemma":[0.0001525586,0.0004385666,0.000359474,0.001626228,0.0002077569,0.0002020687,0.0004050124,0.0003130811,0.003079469],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008021462,"about_ca_system_score_gemma":0.00003963978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008157337,"about_ca_topic_score_gemma":0.001395465,"domain_scores_codex":[0.9972727,0.0001991085,0.0006361656,0.0008006421,0.0002152807,0.0008761449],"domain_scores_gemma":[0.9991413,0.0001380653,0.0002585957,0.0003156161,0.00001581926,0.0001306362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003992355,0.0006373409,0.01291276,0.006940878,0.0002051565,0.0001919197,0.0008550708,0.0002256011,0.0001007604,0.01374205,0.03137434,0.9324149],"study_design_scores_gemma":[0.0002484168,0.0001710546,0.01428331,0.001635985,0.0005854217,0.0001141632,0.00009507222,0.002285362,9.3835e-7,0.00006741983,0.9798969,0.0006159772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0211396,0.9576457,0.0001034894,0.0004173168,0.00307201,0.00241457,0.002397581,0.000333384,0.01247633],"genre_scores_gemma":[0.005231789,0.9870932,0.0004831662,0.00008218663,0.000593274,0.001160616,0.001336855,0.0001149136,0.003903974],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9485225,"threshold_uncertainty_score":0.9998066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1854740689639159,"score_gpt":0.367129258502369,"score_spread":0.1816551895384531,"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."}}