{"id":"W4394888868","doi":"10.21203/rs.3.rs-4248340/v1","title":"Early warning of complex climate risk with integrated artificial intelligence","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Warning system; Situation awareness; Risk analysis (engineering); Computer science; Geospatial analysis; Transformative learning; Hazard; Data science; Management science; Business; Engineering; Geography; Psychology","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":[0.0006444593,0.0003984839,0.0003983027,0.0004315005,0.000221132,0.001576301,0.0005830234,0.000609958,0.003163831],"category_scores_gemma":[0.004048297,0.0001788149,0.0003779031,0.0004009268,0.0004104264,0.001496426,0.001783951,0.00105492,0.0003275434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003923119,"about_ca_system_score_gemma":0.0004531762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003292208,"about_ca_topic_score_gemma":0.00315059,"domain_scores_codex":[0.9997373,0.0001153112,0.00001709931,0.00003353615,0.00007660311,0.00002011075],"domain_scores_gemma":[0.9993165,0.0004158714,0.00006170374,0.00008225845,0.00008251238,0.00004110787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001328584,0.000108559,0.003591005,0.0000996583,0.00009210287,0.0001398562,0.0002218793,0.8409778,0.00302479,0.0358589,0.006942805,0.1088098],"study_design_scores_gemma":[0.000005504985,0.0000104435,0.0002650379,0.000009394217,0.000005837855,0.000009026312,0.00001446408,0.9849118,0.0003963348,0.01274664,0.001619715,0.000005827686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08196946,0.0006928812,0.8931671,0.002920314,0.0002794141,0.00008826854,0.0004862902,0.003996353,0.01639998],"genre_scores_gemma":[0.83772,0.0004510327,0.1573714,0.0002299672,0.0001492591,0.00008045768,0.0004267568,0.0001120125,0.003459132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003292208,"threshold_uncertainty_score":0.01058412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1649671843412402,"score_gpt":0.375378809622652,"score_spread":0.2104116252814118,"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."}}