{"id":"W1929047866","doi":"10.1002/wcc.344","title":"Climate change tipping points: origins, precursors, and debates","year":2015,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Climate Change","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Tipping point (physics); Climate change; Metaphor; Situated; Context (archaeology); Value (mathematics); Epistemology; Sociology; Confusion; Positive economics; Environmental ethics; History; Economics; Psychology; Computer science; Philosophy; Archaeology; Ecology","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":[],"category_scores_codex":[0.001484377,0.000455112,0.0006743229,0.0000897488,0.000356312,0.0001003154,0.0005065376,0.0001380902,0.0002703071],"category_scores_gemma":[0.00004016492,0.0003447676,0.0001492283,0.00035523,0.0002236805,0.0009799523,0.002917853,0.0002258078,0.002393248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003446725,"about_ca_system_score_gemma":0.000004467918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007848463,"about_ca_topic_score_gemma":0.0004690403,"domain_scores_codex":[0.9970794,0.0002164907,0.0006949867,0.0008021261,0.0003193992,0.0008875525],"domain_scores_gemma":[0.9985343,0.00004604028,0.0003577333,0.0005848547,0.00002092924,0.000456195],"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":[0.0004383356,0.001127198,0.4103237,0.005950083,0.00008372985,0.000408227,0.07774919,0.00001443849,0.001943922,0.003621437,0.02001965,0.47832],"study_design_scores_gemma":[0.005651411,0.004528963,0.1192013,0.04579498,0.0006926702,0.002023083,0.01313542,0.06221674,0.0002759643,0.007699712,0.7306054,0.008174432],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8808971,0.07271879,0.00006027165,0.006021811,0.002703473,0.006127968,0.0004092891,0.000403221,0.03065806],"genre_scores_gemma":[0.7815188,0.2121359,0.001418505,0.001553768,0.001000384,0.001895509,0.0001596585,0.0001437691,0.0001737566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7105857,"threshold_uncertainty_score":0.9999005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06976531810345307,"score_gpt":0.3151412476282224,"score_spread":0.2453759295247694,"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."}}