{"id":"W3036080139","doi":"","title":"Visualizing Unquantifiable Uncertainty in Drug Checking Test Results","year":2019,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Visualization; Space (punctuation); Test (biology); Harm; Harm reduction; Data science; Risk analysis (engineering); Data mining; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00927467,0.0004153094,0.0005214667,0.0004791187,0.0002346423,0.001426559,0.003526064,0.0002653188,0.00003877805],"category_scores_gemma":[0.003834026,0.0004573854,0.0001784932,0.001173615,0.0001315286,0.0004759098,0.00388991,0.0007991421,0.0001948897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002297002,"about_ca_system_score_gemma":0.000575616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0023244,"about_ca_topic_score_gemma":0.002280416,"domain_scores_codex":[0.9933388,0.00307603,0.001002883,0.001381712,0.0006561124,0.0005444502],"domain_scores_gemma":[0.9913582,0.002409135,0.0008107641,0.003729263,0.001508915,0.0001836966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002318642,0.002491938,0.009874011,0.0008986858,0.0001193781,0.00004702178,0.0353915,0.02096758,0.002081937,0.8739982,0.0198933,0.03421329],"study_design_scores_gemma":[0.0009210336,3.929782e-7,0.001301688,0.003436232,0.00001718417,0.000004825171,0.0001620056,0.9397225,0.01023126,0.003782748,0.03970893,0.0007111761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01401067,0.000673403,0.8625584,0.01258347,0.000868618,0.0008305085,0.0003364682,0.00061998,0.1075185],"genre_scores_gemma":[0.9147632,0.0007025669,0.05393215,0.0004136315,0.00003827053,0.00003116559,0.001742511,0.00006766713,0.02830883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9187549,"threshold_uncertainty_score":0.9997878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02468441077023604,"score_gpt":0.2797466382402639,"score_spread":0.2550622274700278,"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."}}