{"id":"W3164791059","doi":"10.1109/mim.2021.9436102","title":"Machine Learning in Measurement Part 2: Uncertainty Quantification","year":2021,"lang":"en","type":"article","venue":"IEEE Instrumentation & Measurement Magazine","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Usability; Computer science; Measurement uncertainty; Uncertainty quantification; Software deployment; Artificial intelligence; Risk analysis (engineering); Machine learning; Human–computer interaction; Software engineering; Mathematics; Statistics","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":[0.003410068,0.001812927,0.001297308,0.002177406,0.0009868466,0.004231815,0.001472448,0.003605973,0.01738364],"category_scores_gemma":[0.01051699,0.0009336238,0.001349916,0.003031627,0.004898002,0.005839667,0.002875332,0.006986867,0.006709543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002389019,"about_ca_system_score_gemma":0.001512235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00125421,"about_ca_topic_score_gemma":0.0005719839,"domain_scores_codex":[0.9963631,0.00122938,0.0002116344,0.0007217843,0.001293629,0.0001805089],"domain_scores_gemma":[0.9938619,0.00412376,0.0004093942,0.0006797093,0.0007850424,0.0001403014],"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":[0.00004207446,0.00005820984,0.0007681146,0.0009399647,0.00007538914,0.0002270692,0.0003062311,0.01528095,0.001733201,0.7309477,0.08283391,0.1667872],"study_design_scores_gemma":[0.000008751827,0.00008941571,0.001223996,0.0008571445,0.00004139146,0.0006073011,0.00007809477,0.0249244,0.002057068,0.6386939,0.3313304,0.00008828721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00198962,0.06891373,0.8406569,0.01606308,0.007569502,0.0001895268,0.0008330785,0.0005303005,0.06325424],"genre_scores_gemma":[0.2130087,0.1866351,0.3983792,0.02253402,0.06069162,0.00162979,0.002882062,0.002113079,0.1121265],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01738364,"threshold_uncertainty_score":0.05815405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06298068963506236,"score_gpt":0.2769282678517717,"score_spread":0.2139475782167093,"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."}}