{"id":"W2917647106","doi":"10.1002/qre.1040","title":"Discussion (3): Jones–Johnson Paper","year":2009,"lang":"en","type":"article","venue":"Quality and Reliability Engineering International","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003694612,0.0001292554,0.0001309429,0.00007732773,0.00006547561,0.0000882897,0.0003278674,0.00006668803,0.00002558725],"category_scores_gemma":[0.0003789171,0.00009550356,0.00005189916,0.0001472315,0.00002264369,0.0007703034,0.00009319519,0.0001586173,0.000009286021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008941808,"about_ca_system_score_gemma":0.00001602773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007900887,"about_ca_topic_score_gemma":4.142087e-7,"domain_scores_codex":[0.9988758,0.00003839891,0.0002808269,0.0003723603,0.0002790359,0.0001535878],"domain_scores_gemma":[0.9993433,0.0000873462,0.00006000908,0.0002944025,0.0001272144,0.0000877738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005166218,0.000662609,0.00158478,0.00006291278,0.00004705768,0.00001301858,0.001569903,0.460995,0.006323259,0.3683076,0.0003937776,0.1599885],"study_design_scores_gemma":[0.000566775,0.00006102091,0.1391202,0.00003525893,0.00000267828,0.00001556803,0.0000170391,0.83173,0.000642212,0.008512168,0.01896582,0.000331288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003421244,0.00003389565,0.9844704,0.01041389,0.0006615291,0.0001015331,0.00000503609,0.0002399267,0.0006525941],"genre_scores_gemma":[0.5754537,0.00008304198,0.4230868,0.000711292,0.0001606014,0.00001111948,0.00001486983,0.000009102434,0.0004695083],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5720325,"threshold_uncertainty_score":0.3894522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011034141712088,"score_gpt":0.2827743241702551,"score_spread":0.2717401824581671,"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."}}