{"id":"W3173854030","doi":"10.1145/3466612","title":"Responsible computing during COVID-19 and beyond","year":2021,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada); Western University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer science; Data science; Virology; 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":["metaresearch","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0002855175,0.00006651396,0.00009772689,0.00006877215,0.0006238611,0.0001056149,0.006704425,0.00003059808,0.00005758115],"category_scores_gemma":[0.01280354,0.00005461895,0.00003575781,0.0005716846,0.000217784,0.0003154354,0.02766342,0.0001162845,0.00001929921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001415102,"about_ca_system_score_gemma":0.00006812662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001569706,"about_ca_topic_score_gemma":0.0001814049,"domain_scores_codex":[0.9994628,0.00003065792,0.0001803125,0.0001269026,0.0001000085,0.00009926476],"domain_scores_gemma":[0.988648,0.0002382734,0.0001504659,0.01079223,0.0001614054,0.00000962139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001049844,0.0006194746,0.2820601,0.001859859,0.0001528364,0.00000795794,0.001074093,0.0005072271,0.05738227,0.545768,0.09891321,0.01154994],"study_design_scores_gemma":[0.0008326902,0.000003569833,0.2058571,0.0002819405,0.0001554436,0.00005681027,0.002048136,0.004145763,0.009838488,0.3453155,0.4309855,0.0004791203],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7368357,0.003532956,0.0002663601,0.2413975,0.0002724232,0.0002049559,0.00001453957,0.00009860485,0.01737696],"genre_scores_gemma":[0.9868116,0.0001914423,0.01055397,0.002097785,0.00006633189,0.000002988771,0.00002309995,0.000008703316,0.0002440594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3320722,"threshold_uncertainty_score":0.9986698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1235530269090846,"score_gpt":0.3460163660981547,"score_spread":0.2224633391890702,"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."}}