{"id":"W4388926003","doi":"10.5194/amt-2023-231-supplement","title":"Supplementary material to \"Cost Effective Off-Grid Automatic Precipitation Samplers for Pollutant and Biogeochemical Atmospheric Deposition\"","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Forest Service; Memorial University of Newfoundland; Natural Resources Canada; York University","funders":"Environment and Climate Change Canada","keywords":"Biogeochemical cycle; Environmental science; Deposition (geology); Pollutant; Precipitation; Grid; Environmental chemistry; Meteorology; Chemistry; Geology; Geography; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000855941,0.002000752,0.001150201,0.001205665,0.0004033045,0.001158668,0.002799449,0.001527176,0.7303523],"category_scores_gemma":[0.006699143,0.0009310489,0.0008307889,0.001677464,0.0001930629,0.00136841,0.001274024,0.0008958631,0.2699232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006319098,"about_ca_system_score_gemma":0.0007853661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004156597,"about_ca_topic_score_gemma":0.005169464,"domain_scores_codex":[0.9994519,0.00009582693,0.000059897,0.0001153634,0.0001985883,0.00007828158],"domain_scores_gemma":[0.9971713,0.001242902,0.0001207609,0.0004975266,0.0008085013,0.0001589959],"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":[0.0002621433,0.0002433626,0.0005068393,0.0005552713,0.00006939247,0.0001090261,0.00002074685,0.003577993,0.002934438,0.002964407,0.95459,0.03416634],"study_design_scores_gemma":[0.002324995,0.0004552919,0.01055617,0.0002024755,0.00008788666,0.0005608754,0.000100351,0.1002851,0.02367876,0.03479892,0.826722,0.0002271356],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005733616,0.0003039255,0.09297547,0.001789613,0.005792023,0.0004691941,0.8362719,0.02497355,0.03169063],"genre_scores_gemma":[0.03672939,0.0005002454,0.0663913,0.001132868,0.001793638,0.001041553,0.8122887,0.01261795,0.06750431],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7303523,"threshold_uncertainty_score":0.3846197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357361910511159,"score_gpt":0.2835416596674644,"score_spread":0.2599680405623528,"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."}}