{"id":"W6924988081","doi":"10.16904/envidat.199","title":"Predicted cloud droplet numbers Davos Wolfgang","year":2020,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Aerosol; Bin; Supersaturation; Particle (ecology); Wind speed; Particle number","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":[0.0003383294,0.0009374731,0.0005984466,0.0009617318,0.0002492137,0.0009737803,0.0005720349,0.0006374193,0.004601615],"category_scores_gemma":[0.001242745,0.0003066685,0.0007285126,0.000762929,0.0001441358,0.001004765,0.0005146092,0.0004087001,0.00366141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009537135,"about_ca_system_score_gemma":0.0004702902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02426178,"about_ca_topic_score_gemma":0.01944923,"domain_scores_codex":[0.9997002,0.00002462115,0.00001181505,0.000148334,0.00006022448,0.00005488786],"domain_scores_gemma":[0.9997815,0.00004008195,0.00003179776,0.00004688786,0.00006206978,0.00003759183],"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":[0.0008835137,0.0001771995,0.271634,0.0005384688,0.0004983357,0.0009538067,0.0002558589,0.5526271,0.01686491,0.007979244,0.07672852,0.07085913],"study_design_scores_gemma":[0.0002310627,0.0001611381,0.1602357,0.0002495602,0.0001151462,0.0003424711,0.0003672029,0.7295243,0.02213757,0.007839672,0.07863688,0.0001594304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.8708602,0.001678168,0.01554446,0.0005102339,0.0003407393,0.0001101744,0.08735881,0.003632723,0.01996448],"genre_scores_gemma":[0.9360266,0.0005078443,0.007966349,0.0000761979,0.00006383267,0.0001130927,0.05022012,0.0006400849,0.004385871],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02426178,"threshold_uncertainty_score":0.04824108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03372421184731816,"score_gpt":0.305310165687495,"score_spread":0.2715859538401768,"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."}}