{"id":"W4220856428","doi":"10.1145/3490699","title":"Explainable AI","year":2022,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence","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":[0.002815654,0.0007011928,0.0006612291,0.0007152032,0.001940592,0.004299271,0.002139393,0.002980252,0.03353887],"category_scores_gemma":[0.01822171,0.0004483759,0.001116957,0.0006513747,0.006824207,0.01056224,0.003787038,0.005467719,0.003817786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002441715,"about_ca_system_score_gemma":0.002074405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003946685,"about_ca_topic_score_gemma":0.002907913,"domain_scores_codex":[0.9971719,0.00132565,0.0001115004,0.0005442247,0.0005637522,0.0002829164],"domain_scores_gemma":[0.9930754,0.004166107,0.0002144288,0.001731403,0.0006029518,0.0002098254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001399947,0.000008442899,0.00009343044,0.00005003819,0.0000123374,0.00003330501,0.0001634255,0.001111904,0.0001037539,0.980914,0.01175766,0.005737619],"study_design_scores_gemma":[0.00000976882,0.000003623921,0.00003575529,0.00003708051,0.000008450775,0.0000324991,0.00005649628,0.003610218,0.0001609514,0.9616036,0.03443475,0.000006767709],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01237473,0.006191936,0.5188053,0.1308431,0.003124182,0.0001636366,0.001492594,0.002809481,0.3241952],"genre_scores_gemma":[0.7412856,0.005284748,0.1249942,0.01790649,0.001995209,0.0004635863,0.001612015,0.001398416,0.1050599],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03353887,"threshold_uncertainty_score":0.1121987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06428448530113892,"score_gpt":0.3125194892288825,"score_spread":0.2482350039277435,"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."}}