{"id":"W4367721852","doi":"10.1109/mmul.2023.3272513","title":"Interpretability of Machine Learning: Recent Advances and Future Prospects","year":2023,"lang":"en","type":"article","venue":"IEEE Multimedia","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Interpretability; Computer science; Black box; Representation (politics); Artificial intelligence; Machine learning; Deep learning; Multimedia; Data science","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":[0.005521724,0.000862397,0.001091581,0.001731805,0.0004331176,0.003443372,0.001355061,0.002167339,0.003175006],"category_scores_gemma":[0.01133683,0.0005079826,0.0006446912,0.001604445,0.003426726,0.006170594,0.001954343,0.004012408,0.0008055458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001323017,"about_ca_system_score_gemma":0.0007611296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006230643,"about_ca_topic_score_gemma":0.0004124718,"domain_scores_codex":[0.9985055,0.000662477,0.00009475139,0.000268063,0.0003875939,0.00008170558],"domain_scores_gemma":[0.9839864,0.01399518,0.0004127617,0.0004931345,0.0009334136,0.0001791511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00016502,0.0001178132,0.001620104,0.003196099,0.0001040387,0.0002182077,0.0003879979,0.01143311,0.001102465,0.2844854,0.01282877,0.684341],"study_design_scores_gemma":[0.00003677313,0.0002791594,0.001919059,0.00256913,0.0001031962,0.0008037706,0.0005698962,0.05626234,0.002102185,0.6920959,0.2431315,0.0001270771],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00397004,0.9285595,0.04143521,0.01438938,0.000654293,0.00001554357,0.00004864902,0.00008245368,0.01084485],"genre_scores_gemma":[0.1102598,0.85706,0.02027946,0.002278711,0.007546505,0.00004836319,0.0001251598,0.00005633244,0.002345698],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005521724,"threshold_uncertainty_score":0.02920204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01164153988526008,"score_gpt":0.2705647319119951,"score_spread":0.2589231920267351,"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."}}