{"id":"W3137174455","doi":"10.3138/cart-2020-0027","title":"Geovisualization of COVID-19: State of the Art and Opportunities","year":2021,"lang":"fr","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001744676,0.0002370188,0.0003710405,0.0006245698,0.0004220831,0.0002459527,0.000327354,0.0001291615,0.0001348616],"category_scores_gemma":[0.001795707,0.0001762163,0.0003267692,0.0006969036,0.0009383734,0.0009814431,0.0002015608,0.0002348144,0.000001342292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005549673,"about_ca_system_score_gemma":0.0008718258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006302944,"about_ca_topic_score_gemma":0.00008979228,"domain_scores_codex":[0.9969495,0.0003401285,0.001312594,0.0001733426,0.0009534272,0.0002710418],"domain_scores_gemma":[0.9944733,0.0003807713,0.001375194,0.0002997355,0.003169158,0.0003018025],"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":[0.00190645,0.0007533703,0.2172003,0.005549883,0.004491545,0.00003988078,0.01392756,0.005307378,0.001009526,0.4892603,0.04571765,0.2148362],"study_design_scores_gemma":[0.004010511,0.000285285,0.05463683,0.001138657,0.0007022616,0.001041348,0.004695108,0.01811828,0.0008842112,0.01416369,0.8999629,0.0003608988],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.584483,0.06845696,0.2019566,0.1087769,0.0203199,0.003899343,0.009896834,0.000146995,0.002063462],"genre_scores_gemma":[0.8849102,0.09965941,0.0003014788,0.0101363,0.0004787725,0.00005273139,0.002804303,0.00004076542,0.001616073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8542452,"threshold_uncertainty_score":0.7185894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02726653386274161,"score_gpt":0.3220910421274416,"score_spread":0.2948245082647,"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."}}