{"id":"W4393004895","doi":"10.1561/0200000113","title":"Predictive Global Sensitivity Analysis: Foundational Concepts, Tools, and Applications","year":2024,"lang":"en","type":"article","venue":"Foundations and Trends® in Technology Information and Operations Management","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Gilead Sciences (Canada)","funders":"","keywords":"Sensitivity (control systems); Computer science; Data science; Management science; Engineering","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":[0.0007130121,0.0001277294,0.0001721608,0.001767412,0.0003513848,0.0009659455,0.0000962972,0.00009451407,0.00007514191],"category_scores_gemma":[0.0001165143,0.0001086593,0.00003179201,0.003428164,0.0002523419,0.001468096,0.0001391765,0.0001152045,0.00003301903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007404335,"about_ca_system_score_gemma":0.00002879656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000182984,"about_ca_topic_score_gemma":0.0002196499,"domain_scores_codex":[0.9987867,0.00004042314,0.0004977346,0.0003004063,0.0002382016,0.000136511],"domain_scores_gemma":[0.9993925,0.0001484143,0.00004560775,0.0002333073,0.0001288583,0.0000513089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002288157,0.00001594535,0.001172725,0.000009058272,0.000106483,0.000001379694,0.0001260677,0.0134625,4.336924e-7,0.6540824,0.0001879778,0.3308327],"study_design_scores_gemma":[0.0004419457,0.00005128685,0.1134088,0.00002559124,0.0002771333,0.00003792591,0.002605254,0.7446538,0.000001534243,0.04409358,0.09414899,0.000254217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004980039,0.000379435,0.9836878,0.003231955,0.00009575947,0.0003601861,0.0002362234,0.0001871306,0.006841457],"genre_scores_gemma":[0.9900345,0.0002297896,0.008579731,0.00008911239,0.00001782026,0.0002682023,0.000377951,0.000002908122,0.0003999467],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9850545,"threshold_uncertainty_score":0.9314634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02582304636302766,"score_gpt":0.3378309512395788,"score_spread":0.3120079048765511,"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."}}