{"id":"W3157108190","doi":"10.1386/jdmp_00052_1","title":"Municipal digital infrastructure and the COVID-19 pandemic: A case study of Calgary, Canada","year":2021,"lang":"en","type":"article","venue":"Journal of Digital Media & Policy","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Pandemic; Service provider; Work (physics); The Internet; Public relations; General partnership; Private sector; Business; Service (business); Population; Coronavirus disease 2019 (COVID-19); Public administration; Political science; Economic growth; Sociology; Engineering; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001127251,0.0005324639,0.0005303018,0.001800064,0.03480778,0.005746017,0.002957267,0.002545825,0.003924117],"category_scores_gemma":[0.003072249,0.0004610744,0.0004012626,0.006621521,0.006939203,0.001355045,0.00626502,0.003371968,0.0002594223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1202796,"about_ca_system_score_gemma":0.1392637,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955539,"about_ca_topic_score_gemma":0.9985662,"domain_scores_codex":[0.9974028,0.0005058151,0.00005162696,0.0001278645,0.0003516621,0.001560149],"domain_scores_gemma":[0.997902,0.0004670949,0.0001769156,0.00008212408,0.0005222512,0.0008496739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001894421,0.0007336211,0.1758411,0.0006727607,0.0001350888,0.05160519,0.6175081,0.003167251,0.001398602,0.05792627,0.03943543,0.05138722],"study_design_scores_gemma":[0.00001698772,0.00004962723,0.04100917,0.0002670893,0.00003241366,0.0009895315,0.9125279,0.0007124892,0.0001554048,0.0007182373,0.04347747,0.00004359669],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9450049,0.001816124,0.0005303572,0.01041566,0.00009097742,0.0003013438,0.0005340084,0.00002304751,0.04128359],"genre_scores_gemma":[0.987152,0.00194256,0.0005212863,0.001646499,0.00001427456,0.00006693305,0.0001694045,0.00001955902,0.008467467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1202796,"threshold_uncertainty_score":0.872694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01891610223596158,"score_gpt":0.2517395196897268,"score_spread":0.2328234174537652,"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."}}