{"id":"W3136788967","doi":"10.1109/tcss.2021.3058633","title":"The Pandemic Holiday Blip in New York City","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Social Systems","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Pandemic; Economic shortage; Coronavirus disease 2019 (COVID-19); Computer science; Health care; Operations research; Risk analysis (engineering); Service (business); Representation (politics); Healthcare system; Simulation; Computer security; Engineering; Business; Disease; Medicine; Economics; Political science; Economic growth; Marketing; Infectious disease (medical specialty)","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":[],"consensus_categories":[],"category_scores_codex":[0.000745513,0.0001637084,0.000358852,0.00004396675,0.0007863525,0.00007522643,0.0001576404,0.000139965,0.00003622714],"category_scores_gemma":[0.0001905351,0.0001260868,0.0001866634,0.000468795,0.00009186499,0.00004306214,0.000003270975,0.0003488048,0.00003897665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003600149,"about_ca_system_score_gemma":0.0002777661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007930867,"about_ca_topic_score_gemma":0.001802863,"domain_scores_codex":[0.9980035,0.0004869331,0.0005440818,0.0002876712,0.0003977672,0.000279991],"domain_scores_gemma":[0.9928618,0.006692514,0.0001402096,0.0001216738,0.0001135904,0.00007022009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002975607,0.001458761,0.01202075,0.0003345696,0.001059231,0.00005824709,0.00747189,0.6950033,0.0001438809,0.1570707,0.05551425,0.06956682],"study_design_scores_gemma":[0.004366148,0.0001956606,0.03959126,0.0003711508,0.0002201198,0.00006020917,0.004026999,0.05465294,0.0001160408,0.8208531,0.07410835,0.00143798],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03995778,0.0004837843,0.9524065,0.004273131,0.001336795,0.0004389673,0.00003909027,0.0001896059,0.0008743126],"genre_scores_gemma":[0.9974538,0.00003377118,0.0005433278,0.0002943244,0.0003190532,0.00006098617,0.000002961091,0.00001489709,0.001276868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.957496,"threshold_uncertainty_score":0.6048067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3302494852638138,"score_gpt":0.4189687156241469,"score_spread":0.08871923036033313,"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."}}