{"id":"W4323565362","doi":"10.3390/make5010017","title":"Painting the Black Box White: Experimental Findings from Applying XAI to an ECG Reading Setting","year":2023,"lang":"en","type":"article","venue":"Machine Learning and Knowledge Extraction","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ministero della Salute; Università degli Studi di Siena","keywords":"Usability; Computer science; Perception; Relevance (law); Transparency (behavior); Reading (process); Data science; Human–computer interaction; Psychology; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001767361,0.0002210927,0.0001750634,0.0002392184,0.00136595,0.0007025484,0.0004142213,0.00008645751,0.00004017124],"category_scores_gemma":[0.0004407851,0.0001954172,0.00005604854,0.0008565997,0.00004689288,0.0008588991,0.0003757491,0.0006164471,0.0005421937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000983256,"about_ca_system_score_gemma":0.00002761625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004581802,"about_ca_topic_score_gemma":0.0001131353,"domain_scores_codex":[0.9979512,0.0003579533,0.0003205463,0.000651538,0.0002272906,0.0004914391],"domain_scores_gemma":[0.9988155,0.0005432183,0.0001191968,0.0003030649,0.00006746842,0.0001514897],"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":[0.000041922,0.0001544199,0.05734652,0.00004119879,0.00004165065,0.00004625931,0.1071003,0.01091111,0.2698674,0.002508596,0.001138738,0.5508019],"study_design_scores_gemma":[0.0001005886,0.0001297619,0.003970169,0.00008815331,0.000008493915,0.00001366737,0.01343089,0.9341962,0.03401347,0.0003739721,0.0133593,0.0003152701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8414201,0.0002427331,0.1526195,0.001095654,0.0006379332,0.000327931,0.000001306793,0.0009125536,0.002742325],"genre_scores_gemma":[0.9918453,0.00001280308,0.005797698,0.0001001956,0.0003469791,0.00005577051,0.00001788057,0.0000333693,0.001789974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9232851,"threshold_uncertainty_score":0.9999341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02306900827253041,"score_gpt":0.3251711536382746,"score_spread":0.3021021453657443,"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."}}