{"id":"W4401518254","doi":"10.3390/cli12080119","title":"Advanced Forecasting of Drought Zones in Canada Using Deep Learning and CMIP6 Projections","year":2024,"lang":"en","type":"article","venue":"Climate","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université Laval","funders":"","keywords":"Environmental science; Climate change; Zoning; Precipitation; Climatology; Water resources; Environmental resource management; Agriculture; Sample (material); Meteorology; Geography; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003223557,0.0005563418,0.0002072788,0.0009680353,0.000687745,0.0007124535,0.0006369435,0.000306973,0.001267905],"category_scores_gemma":[0.001105316,0.0001845453,0.0003512772,0.001668773,0.0002285527,0.0004414633,0.0004320813,0.0005271894,0.0001502215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01394151,"about_ca_system_score_gemma":0.01345497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.982715,"about_ca_topic_score_gemma":0.9833657,"domain_scores_codex":[0.9998637,0.000008849632,0.000005349768,0.00002522442,0.00004606586,0.00005073522],"domain_scores_gemma":[0.9996232,0.00002706874,0.00002843496,0.00001113955,0.0002553703,0.00005474255],"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":[0.0001906083,0.00008904828,0.1259266,0.0001357824,0.0001299695,0.0002116649,0.0001352708,0.7888761,0.001893366,0.004057007,0.02008579,0.05826895],"study_design_scores_gemma":[0.00001574777,0.000006009289,0.04383181,0.0000198142,0.00002082829,0.000008995094,0.0001263274,0.9505821,0.0007081784,0.0006509221,0.004006902,0.00002220137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9361458,0.001056574,0.01695505,0.001755817,0.0001100617,0.00005838366,0.03283929,0.001048039,0.01003091],"genre_scores_gemma":[0.9803547,0.0005433263,0.006569373,0.00006564162,0.00001209699,0.00001401943,0.01076917,0.00002825382,0.001643331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01728505,"threshold_uncertainty_score":0.1011532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230988119052658,"score_gpt":0.2426747887746481,"score_spread":0.2303649075841215,"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."}}