{"id":"W3080961046","doi":"10.1109/dsc50466.2020.00005","title":"Message from the General ChairsDSC 2020","year":2020,"lang":"en","type":"article","venue":"","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cyberspace; Pleasure; China; Computer science; World Wide Web; Telecommunications; The Internet; Library science; Political science; Psychology","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":[0.003357537,0.001088642,0.000799851,0.0006316599,0.0023424,0.004542307,0.001272833,0.01133415,0.1042507],"category_scores_gemma":[0.008761015,0.000386511,0.0008271494,0.0006787013,0.0006375065,0.002225979,0.00201249,0.01175733,0.1056464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003064926,"about_ca_system_score_gemma":0.007799661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009351688,"about_ca_topic_score_gemma":0.01515884,"domain_scores_codex":[0.9982734,0.0002138068,0.00009259446,0.0002836148,0.0008224075,0.0003141902],"domain_scores_gemma":[0.9935541,0.000380917,0.0001647638,0.0001596312,0.003695289,0.002045328],"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":[0.00001631229,0.000005266981,0.00003302416,0.00001782464,8.005664e-7,0.00001253768,0.000003309375,0.000007445185,0.00003404985,0.0002129825,0.9976419,0.002014512],"study_design_scores_gemma":[0.00001350854,0.00001526319,0.0003460418,0.00004359732,0.00000264214,0.0000248398,0.00003802978,0.00002938204,0.0001048247,0.0002283422,0.9991442,0.000009344303],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.000613747,0.003218785,0.0008687555,0.4789781,0.4650649,0.000258904,0.002734313,0.0006370891,0.04762533],"genre_scores_gemma":[0.004972576,0.00229434,0.0007063961,0.5004408,0.06275524,0.0003472091,0.002406923,0.0004300478,0.4256465],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.1042507,"threshold_uncertainty_score":0.3487533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2914835952647328,"score_gpt":0.3795147392486793,"score_spread":0.08803114398394651,"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."}}