{"id":"W3049425455","doi":"10.1111/exsy.12621","title":"Visual interpretation of regression error","year":2020,"lang":"en","type":"article","venue":"Expert Systems","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Fundação para a Ciência e a Tecnologia; Canada Research Chairs","keywords":"Computer science; Machine learning; Black box; Context (archaeology); Artificial intelligence; Visualization; Reliability (semiconductor); Regression; Interpretation (philosophy); Regression analysis; Point (geometry); Data mining; Data science; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001670952,0.0001050362,0.0001970061,0.00005580638,0.00005572195,0.00007558778,0.0005581649,0.00005399383,0.00001322221],"category_scores_gemma":[0.0001292833,0.00008616186,0.00005606343,0.0003259863,0.00002961777,0.000491489,0.0001431172,0.00006685252,0.0001637075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003124338,"about_ca_system_score_gemma":0.00003612687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000200048,"about_ca_topic_score_gemma":0.000002800058,"domain_scores_codex":[0.9987673,0.0001188269,0.000363843,0.0002891273,0.0002938988,0.0001670572],"domain_scores_gemma":[0.9992819,0.00007058769,0.0001603459,0.0002701397,0.0001133993,0.0001035633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000221582,0.0003363935,0.0009920897,0.0004439637,0.00009016097,0.0001222635,0.2069019,0.006402556,0.5197852,0.1384923,0.03772769,0.08848387],"study_design_scores_gemma":[0.00005722706,0.0001852034,0.00002015207,0.0001331999,0.00000100324,0.000004801072,0.00212561,0.8848681,0.1079942,0.00008471413,0.004406821,0.0001189082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02971022,0.001061128,0.9638608,0.001574331,0.001114479,0.0002611133,7.79224e-7,0.0002004104,0.002216746],"genre_scores_gemma":[0.9974633,0.000007614658,0.001889991,0.000345947,0.0001572587,0.0000224225,0.000001276602,0.000008745771,0.0001034107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9677531,"threshold_uncertainty_score":0.3513579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04896243409861682,"score_gpt":0.3323753275942494,"score_spread":0.2834128934956325,"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."}}