{"id":"W3212465629","doi":"10.18280/ria.350509","title":"Unsupervised Convolutional Filter Learning for COVID-19 Classification","year":2021,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoencoder; Coronavirus disease 2019 (COVID-19); Computer science; Artificial intelligence; Convolutional neural network; Filter (signal processing); Identification (biology); Unsupervised learning; Machine learning; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Deep learning; Sensitivity (control systems); Pattern recognition (psychology); Medicine; Engineering; Pathology; Computer vision; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008876294,0.0005946156,0.0005374636,0.0009184123,0.0003442163,0.0005302431,0.0007332999,0.001040853,0.001424563],"category_scores_gemma":[0.002262173,0.0002232848,0.0006728163,0.0007498,0.0002998066,0.0006408209,0.0004746735,0.001091821,0.000818153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008856386,"about_ca_system_score_gemma":0.001249195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01760061,"about_ca_topic_score_gemma":0.01289334,"domain_scores_codex":[0.9996194,0.00006582677,0.00002354115,0.00009924854,0.0001077854,0.00008415454],"domain_scores_gemma":[0.9991702,0.0003814914,0.00006970509,0.00008928359,0.0002524049,0.00003696778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000327567,0.0002501113,0.005937819,0.00009359518,0.0001399263,0.000194306,0.00007138322,0.2651282,0.02293279,0.004924947,0.008058609,0.6919407],"study_design_scores_gemma":[0.000003230753,0.00002313435,0.0007853312,0.000005835062,0.000007752815,0.00003630676,0.000005630597,0.9934948,0.003904289,0.0009187101,0.0008087779,0.000006260358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07822293,0.001119034,0.9130579,0.0005387675,0.0001701611,0.00008745322,0.0005097627,0.002776696,0.003517363],"genre_scores_gemma":[0.6650859,0.0007652846,0.3195978,0.0003216312,0.0001474394,0.0001259827,0.002732534,0.0001312119,0.01109221],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01760061,"threshold_uncertainty_score":0.03499627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1471766052982907,"score_gpt":0.3721287270168919,"score_spread":0.2249521217186012,"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."}}