{"id":"W3068613985","doi":"10.1109/access.2020.3018028","title":"Novel Coronavirus Cough Database: NoCoCoDa","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Élisabeth Bruyère Hospital; Bruyère; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; AGE-WELL","keywords":"Interim; Pandemic; Dry cough; Annotation; Interim analysis; Set (abstract data type); Coronavirus","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005878401,0.0009293181,0.0007907094,0.002426791,0.0005628378,0.0009053745,0.001162499,0.001552627,0.004219697],"category_scores_gemma":[0.003113428,0.0002368599,0.0006386538,0.001673272,0.0002222911,0.000878514,0.001341005,0.0005800212,0.003329299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005269842,"about_ca_system_score_gemma":0.0008302357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005497913,"about_ca_topic_score_gemma":0.009984598,"domain_scores_codex":[0.9993131,0.00009139199,0.0001686657,0.0002220386,0.0001313526,0.00007342377],"domain_scores_gemma":[0.9990371,0.0002405807,0.0001450665,0.0002286382,0.0002306975,0.0001179401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003377179,0.0006200678,0.07179213,0.009937669,0.0004400842,0.003136616,0.001283531,0.005870348,0.02553768,0.002359951,0.7148684,0.1607763],"study_design_scores_gemma":[0.0005857963,0.0007305291,0.2424724,0.001055105,0.0002809377,0.004467188,0.001939266,0.02804902,0.00997744,0.002527048,0.7076067,0.0003085139],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.09628945,0.004086736,0.005607971,0.0004528565,0.0004380722,0.0007831061,0.8792055,0.006246984,0.00688928],"genre_scores_gemma":[0.06886373,0.0007736711,0.01017246,0.0002530695,0.0001144322,0.0008083787,0.9175228,0.0001616167,0.001329861],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005497913,"threshold_uncertainty_score":0.01411635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2019302992843564,"score_gpt":0.4255244126395165,"score_spread":0.22359411335516,"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."}}