{"id":"W6912196052","doi":"10.5281/zenodo.3989347","title":"Better Prepare for Future COVIDs","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Child and Adolescent Health","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"World economy; Lock (firearm); World class; Race (biology); First world war","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":[0.004461807,0.0006619302,0.0004205171,0.001284083,0.005969591,0.009330111,0.001655418,0.007161802,0.2118211],"category_scores_gemma":[0.01751935,0.0003218904,0.0009017703,0.0004794087,0.001829005,0.006142239,0.01125853,0.01198827,0.05918321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002768001,"about_ca_system_score_gemma":0.01828811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005472803,"about_ca_topic_score_gemma":0.009340355,"domain_scores_codex":[0.9949958,0.001329391,0.0001611683,0.0002534107,0.001113508,0.002146621],"domain_scores_gemma":[0.9831503,0.0009838765,0.000704828,0.0005574561,0.002598161,0.01200545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003510525,0.0002729422,0.004201487,0.0001617232,0.00001457595,0.0003897273,0.001047718,0.0001122173,0.0003567619,0.02101373,0.9029188,0.06947523],"study_design_scores_gemma":[0.00001666171,0.00008445383,0.003104311,0.0003740106,0.00000548951,0.0002584423,0.004356359,0.00005472499,0.0001705792,0.006495005,0.9850566,0.00002345679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.009011484,0.004610178,0.003277776,0.789974,0.02588778,0.0003184515,0.0008413833,0.0006454854,0.1654334],"genre_scores_gemma":[0.1055893,0.009435371,0.01067424,0.409004,0.01120852,0.0008407116,0.001999196,0.0008468808,0.4504018],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2118211,"threshold_uncertainty_score":0.7086123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08063310886671138,"score_gpt":0.3516798895311562,"score_spread":0.2710467806644448,"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."}}