{"id":"W4223955143","doi":"10.1016/j.neunet.2022.03.034","title":"Think positive: An interpretable neural network for image recognition","year":2022,"lang":"en","type":"article","venue":"Neural Networks","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Interpretability; Deep learning; Artificial intelligence; Computer science; Machine learning; Transparency (behavior); Gold standard (test); Coronavirus disease 2019 (COVID-19); Artificial neural network; Pneumonia; Medicine; Disease; Infectious disease (medical specialty); Radiology; Pathology; Internal medicine","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":[0.0009209654,0.001174001,0.0005149424,0.0006794161,0.0003367938,0.001160862,0.001847452,0.001475577,0.0115468],"category_scores_gemma":[0.003984834,0.0003716528,0.0007083393,0.0005154693,0.0004765402,0.001342881,0.001009509,0.001523766,0.002089466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005633887,"about_ca_system_score_gemma":0.0005821771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004688168,"about_ca_topic_score_gemma":0.007317668,"domain_scores_codex":[0.99967,0.00007421572,0.00002007888,0.00008771468,0.0001157539,0.0000322998],"domain_scores_gemma":[0.9991764,0.0004383928,0.00006172982,0.00008194541,0.0001990265,0.00004243552],"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":[0.0008928161,0.0002460631,0.002380788,0.0004437469,0.0001737312,0.0004008722,0.0001652732,0.08478118,0.01800043,0.01723189,0.04655153,0.8287317],"study_design_scores_gemma":[0.00003968828,0.00009977948,0.0004721793,0.00004432402,0.00004541154,0.0001002119,0.00003037324,0.970112,0.007072969,0.01676084,0.005204176,0.00001798455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02078336,0.0007842246,0.9536272,0.00122406,0.0005194795,0.0002331399,0.001421832,0.01363621,0.007770595],"genre_scores_gemma":[0.3522097,0.0006866123,0.6235479,0.001298339,0.0002804356,0.0004369754,0.002013092,0.0006945598,0.01883247],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0115468,"threshold_uncertainty_score":0.03862786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0257318857426956,"score_gpt":0.3099001337531738,"score_spread":0.2841682480104782,"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."}}