{"id":"W4292227971","doi":"10.1080/08982112.2022.2106440","title":"Statistical engineering – Part 2: Future","year":2022,"lang":"en","type":"article","venue":"Quality Engineering","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Leverage (statistics); Government (linguistics); Order (exchange); Computer science; Key (lock); Data science; Management science; Operations research; Engineering ethics; Engineering; Economics; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04085879,0.001223673,0.0009879288,0.002473922,0.002195937,0.008513907,0.001867333,0.008408814,0.0117389],"category_scores_gemma":[0.03832243,0.0007308293,0.001319974,0.002617648,0.0108446,0.01553031,0.004030567,0.01072353,0.004836421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004698325,"about_ca_system_score_gemma":0.005693981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001507365,"about_ca_topic_score_gemma":0.001100148,"domain_scores_codex":[0.9847869,0.008501858,0.0007124206,0.001768413,0.003692669,0.0005376068],"domain_scores_gemma":[0.9532437,0.03119883,0.001303295,0.003927981,0.008760512,0.001565672],"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":[0.00005993984,0.0001113972,0.0007173253,0.0006112061,0.00003434575,0.0001195593,0.0006060533,0.001980304,0.0005034803,0.6497653,0.1385139,0.2069771],"study_design_scores_gemma":[0.00001118064,0.0001228051,0.0006789514,0.00110252,0.00001034794,0.0002678061,0.0004258613,0.002015967,0.0003834598,0.397328,0.5976036,0.00004949631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002793614,0.2478077,0.1093726,0.5248994,0.03364383,0.0001335399,0.0002132925,0.0002917882,0.08084413],"genre_scores_gemma":[0.1238977,0.3884755,0.09728117,0.2037015,0.08841778,0.0008952437,0.0005961289,0.0007838713,0.09595117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04085879,"threshold_uncertainty_score":0.2160845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1102379834274348,"score_gpt":0.4173955416998471,"score_spread":0.3071575582724123,"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."}}