{"id":"W3010251753","doi":"10.1177/0846537120913497","title":"COVID-19: What Can We Learn From Stories From the Trenches?","year":2020,"lang":"en","type":"article","venue":"Canadian Association of Radiologists Journal","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Coronavirus Infections; Betacoronavirus; MEDLINE; Virology; Internal medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01234967,0.0009974118,0.000904,0.002573794,0.01481322,0.01388879,0.002901234,0.008106994,0.01204456],"category_scores_gemma":[0.0980734,0.0006524067,0.0006282583,0.002494126,0.01385822,0.01660386,0.008429071,0.02211977,0.003622808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01154355,"about_ca_system_score_gemma":0.01959826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09838787,"about_ca_topic_score_gemma":0.2121363,"domain_scores_codex":[0.9885506,0.006006023,0.0005149537,0.0004508778,0.002665855,0.001811678],"domain_scores_gemma":[0.9341581,0.03712923,0.003464031,0.001311904,0.01256923,0.01136739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000634333,0.00006722363,0.01087358,0.0008550921,0.00005570182,0.00546577,0.2173588,0.00009803197,0.0001973209,0.01960359,0.6762238,0.0691376],"study_design_scores_gemma":[0.00001078134,0.00003113557,0.003005305,0.003241292,0.00003090617,0.004093599,0.286713,0.00008241528,0.0001562944,0.01874868,0.6837833,0.0001033487],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01260177,0.02685301,0.001089018,0.9121953,0.00844224,0.00004249486,0.0004250534,0.00007011941,0.03828093],"genre_scores_gemma":[0.4081796,0.106367,0.005342122,0.4198834,0.02048277,0.0002335829,0.00115535,0.0007307314,0.03762537],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.09838787,"threshold_uncertainty_score":0.1956304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0515421160789499,"score_gpt":0.3026088378815626,"score_spread":0.2510667218026127,"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."}}