{"id":"W7131882108","doi":"10.1109/icstsn67075.2025.11397949","title":"Climate Pattern Detection and Prediction Using Deep Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Deep learning; Feature engineering; Variety (cybernetics); Convolutional neural network; Climate pattern; Climate change; Feature (linguistics); Climate model","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":[0.0005340651,0.000708734,0.0004326271,0.001316758,0.0002770474,0.0008759871,0.0007727241,0.0006446897,0.001586244],"category_scores_gemma":[0.002074727,0.0003274507,0.0006367635,0.001393285,0.0002789581,0.001471225,0.0009584603,0.001103735,0.0004464221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007588569,"about_ca_system_score_gemma":0.0007639771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01162455,"about_ca_topic_score_gemma":0.01387834,"domain_scores_codex":[0.999777,0.00003784208,0.00001758237,0.0000793001,0.00004634785,0.00004186572],"domain_scores_gemma":[0.9994411,0.00021997,0.0001034227,0.00007297144,0.0001246423,0.00003796261],"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":[0.0001040903,0.0001597418,0.02124589,0.0001193452,0.0001488785,0.0001228184,0.0000652089,0.7541856,0.004896994,0.005539549,0.004109001,0.2093028],"study_design_scores_gemma":[0.000002515893,0.000004224231,0.001086187,0.00000544364,0.000003729898,0.000005551165,0.000006551134,0.9952208,0.0005379824,0.002764934,0.0003582979,0.000003693031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1894615,0.001595925,0.7962819,0.001245652,0.0002262981,0.00007918426,0.002486217,0.002988313,0.005635052],"genre_scores_gemma":[0.912771,0.0006365729,0.08224281,0.0001638212,0.00008889045,0.00005722769,0.002233339,0.00007420378,0.001732202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01162455,"threshold_uncertainty_score":0.02311379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01873712058513062,"score_gpt":0.2579153678681689,"score_spread":0.2391782472830383,"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."}}