{"id":"W4391271703","doi":"10.5194/gmd-17-685-2024","title":"Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1","year":2024,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Scavenging; Cloud computing; Chemistry; Environmental science; Meteorology; Physics; Computer science; Organic chemistry; Operating system","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":[0.0005288873,0.0006849637,0.0005046932,0.0002080751,0.0004666225,0.0005575247,0.001775534,0.001067588,0.001301244],"category_scores_gemma":[0.0009100544,0.0004164059,0.0007384954,0.0002977551,0.0003845112,0.0005384035,0.00058425,0.0008015812,0.0002264836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395055,"about_ca_system_score_gemma":0.001316148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09171639,"about_ca_topic_score_gemma":0.07567801,"domain_scores_codex":[0.9998831,0.00002757664,0.000005962644,0.00002815975,0.00002864324,0.00002662206],"domain_scores_gemma":[0.9996696,0.0001133502,0.0000341265,0.00004501937,0.00007691442,0.00006115276],"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":[0.0003378009,0.0003032862,0.02741577,0.00009254261,0.0001170572,0.0001364106,0.0001148958,0.9534667,0.007449721,0.001670586,0.002670798,0.006224422],"study_design_scores_gemma":[0.00005965929,0.00004496166,0.003107044,0.00000344466,0.000008659733,0.000009472584,0.00001410975,0.9949179,0.0009378289,0.0001371196,0.0007494629,0.00001046027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9744529,0.000148453,0.009826329,0.0003201815,0.00008035835,0.00009890037,0.003948772,0.001821739,0.009302373],"genre_scores_gemma":[0.9785237,0.00004953244,0.01652049,0.0001292436,0.00002092509,0.00004645822,0.003287081,0.0001560912,0.001266506],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09171639,"threshold_uncertainty_score":0.1823651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0205578002234211,"score_gpt":0.2153858665312844,"score_spread":0.1948280663078633,"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."}}