{"id":"W4280559094","doi":"10.1088/1748-9326/ac6f6c","title":"Socio-metabolic risk and tipping points on islands","year":2022,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tipping point (physics); Small Island Developing States; Sustainability; Climate change; Vulnerability (computing); Environmental resource management; Business; Framing (construction); Natural resource economics; Leverage (statistics); Psychological resilience; Environmental planning; Risk analysis (engineering); Environmental science; Geography; Economics; Ecology; Computer science; 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":[0.0006531738,0.0003930205,0.0002970007,0.00138188,0.001288378,0.002722144,0.0007315177,0.0007788872,0.006113813],"category_scores_gemma":[0.002681945,0.000126404,0.0004351164,0.001100415,0.003970813,0.002937261,0.004123469,0.001173634,0.0002151614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002389358,"about_ca_system_score_gemma":0.001037898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009731825,"about_ca_topic_score_gemma":0.01229794,"domain_scores_codex":[0.9994389,0.0002546936,0.00002612922,0.00006759762,0.00009842207,0.000114243],"domain_scores_gemma":[0.9987223,0.0005086671,0.000306481,0.00009736961,0.0002201374,0.0001451163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001573235,0.0001127222,0.1324018,0.001919894,0.0002831377,0.003799162,0.05285162,0.02909592,0.00213743,0.6427619,0.005315562,0.1291635],"study_design_scores_gemma":[0.00001446462,0.0002430048,0.2037152,0.003359073,0.0002412393,0.001148189,0.1744799,0.0177121,0.001503656,0.4973207,0.1001296,0.0001328343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8376538,0.005275323,0.02099411,0.01221177,0.0001662756,0.0001240903,0.0006474423,0.00007618447,0.122851],"genre_scores_gemma":[0.9975142,0.0009060957,0.0007737656,0.000102948,0.00001031462,0.00001196982,0.00004333762,0.000004469102,0.0006328234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009731825,"threshold_uncertainty_score":0.0204528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1010231378766863,"score_gpt":0.3478512189509298,"score_spread":0.2468280810742435,"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."}}