{"id":"W4297541772","doi":"10.3390/jrfm15100431","title":"Multi-Criteria Decision Making in Production Fields: A Structured Content Analysis and Implications for Practice","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multiple-criteria decision analysis; Ranking (information retrieval); Decision analysis; Computer science; Production (economics); Work (physics); Domain (mathematical analysis); Automotive industry; Sorting; Business decision mapping; Process (computing); Management science; Decision support system; Operations research; Risk analysis (engineering); Engineering; Business; Mathematics; Artificial intelligence; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06364603,0.001162033,0.001221649,0.00990256,0.004666447,0.01192169,0.002599313,0.003231289,0.003503543],"category_scores_gemma":[0.08668457,0.0006670395,0.0009651286,0.01200066,0.01370431,0.01041364,0.004397611,0.003012721,0.0005249133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01298824,"about_ca_system_score_gemma":0.01584961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003532877,"about_ca_topic_score_gemma":0.004345426,"domain_scores_codex":[0.9423493,0.04549706,0.002513539,0.001348817,0.007454638,0.0008366354],"domain_scores_gemma":[0.8421468,0.1383785,0.004202447,0.003328685,0.0106587,0.001284966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001421253,0.0007386246,0.01090575,0.007661581,0.000153108,0.0009800342,0.07980054,0.01408426,0.001677914,0.5342646,0.009065362,0.3405261],"study_design_scores_gemma":[0.00008370079,0.00023218,0.00560143,0.01421249,0.000080443,0.0004894221,0.1257727,0.03792769,0.001745954,0.7676116,0.04609308,0.0001494136],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.143374,0.01936302,0.6580253,0.08571165,0.0007344082,0.006485214,0.0006173736,0.0002829822,0.08540619],"genre_scores_gemma":[0.548093,0.006024178,0.4409705,0.001185063,0.0001394438,0.002149587,0.0001499311,0.00005372023,0.001234602],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06364603,"threshold_uncertainty_score":0.3365964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161654756505118,"score_gpt":0.421308657559483,"score_spread":0.3051431819089712,"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."}}