{"id":"W4401709626","doi":"10.5194/esd-15-1117-2024","title":"Tipping point detection and early warnings in climate, ecological, and human systems","year":2024,"lang":"en","type":"article","venue":"Earth System Dynamics","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tipping point (physics); Field (mathematics); Data science; Climate change; Computer science; Variety (cybernetics); Set (abstract data type); Warning system; Point (geometry); Ecology; Geography; Environmental resource management; Operations research; Environmental science; Artificial intelligence; Engineering; Mathematics; Telecommunications; Biology","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":[0.01133648,0.001639156,0.001720921,0.0120013,0.0008325914,0.003598207,0.001879212,0.00244489,0.002351747],"category_scores_gemma":[0.05387501,0.0004188256,0.001482524,0.008422884,0.001655376,0.005987165,0.002850081,0.002434005,0.0005185538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001840641,"about_ca_system_score_gemma":0.001648824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005413253,"about_ca_topic_score_gemma":0.004895811,"domain_scores_codex":[0.9893256,0.005220249,0.001198435,0.001115388,0.002649732,0.0004905091],"domain_scores_gemma":[0.9408008,0.04248212,0.006669628,0.001290717,0.008056094,0.0007006271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000549069,0.0002339074,0.1059686,0.01273519,0.001306133,0.0007623101,0.002051083,0.2556022,0.002240101,0.06277066,0.01673353,0.5390472],"study_design_scores_gemma":[0.00008923734,0.001157353,0.1048025,0.007235577,0.0009616722,0.001297684,0.004535121,0.6424572,0.007813071,0.1796963,0.04924841,0.0007059777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1587942,0.1168778,0.6841184,0.006154601,0.001798038,0.000842153,0.005357553,0.001841101,0.02421618],"genre_scores_gemma":[0.8713235,0.01496683,0.1090796,0.0005405036,0.0003812835,0.0003029803,0.001717669,0.00007864029,0.001608947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0120013,"threshold_uncertainty_score":0.05995375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003670557374255477,"score_gpt":0.1940151996078612,"score_spread":0.1903446422336057,"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."}}