{"id":"W4253232939","doi":"10.5194/acp-2017-38-supplement","title":"Supplementary material to \"Classifying aerosol type using in situ surface spectral aerosoloptical properties\"","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Aerosol; In situ; Surface (topology); Chemistry; Mathematics; Organic chemistry; Geometry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009082867,0.001972359,0.001152201,0.002497069,0.0005866275,0.001546587,0.002423093,0.001382787,0.7398473],"category_scores_gemma":[0.008437991,0.0007776669,0.001051224,0.002666306,0.0002549094,0.001564308,0.001581355,0.00101782,0.3306681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006776814,"about_ca_system_score_gemma":0.00127325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005008894,"about_ca_topic_score_gemma":0.006383477,"domain_scores_codex":[0.9994794,0.00006655834,0.00005943727,0.0001151966,0.0001881344,0.00009137094],"domain_scores_gemma":[0.9956797,0.001679311,0.0002022777,0.0007738805,0.001394399,0.0002703329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008991297,0.000195831,0.0005897334,0.0004879315,0.00005422609,0.00007327167,0.00001627634,0.001211463,0.001247737,0.002060307,0.9761173,0.01785603],"study_design_scores_gemma":[0.0008590965,0.0001906833,0.01014438,0.0002968301,0.0000882109,0.0005299306,0.00009524683,0.02011704,0.01097947,0.03330906,0.9232117,0.0001783451],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002140755,0.0001406212,0.01445528,0.0008798258,0.002836987,0.0001687034,0.9542723,0.008418415,0.01668717],"genre_scores_gemma":[0.01095368,0.0003455433,0.02328383,0.0008484085,0.001175322,0.0005078481,0.9207865,0.005056697,0.03704214],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7398473,"threshold_uncertainty_score":0.3710762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04767705127171255,"score_gpt":0.2794757240377325,"score_spread":0.23179867276602,"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."}}