{"id":"W10400430","doi":"","title":"An Analytic Hierarchy Process Approach For Supplier Evaluation and Selection in a Steel Manufacturing Company","year":2007,"lang":"en","type":"dissertation","venue":"","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytic hierarchy process; Purchasing; Selection (genetic algorithm); Operations research; Process (computing); Supplier relationship management; Analytic network process; Computer science; Hierarchy; Management science; Identification (biology); Multiple-criteria decision analysis; Engineering; Operations management; Business; Supply chain management; Supply chain; Marketing; Economics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01067854,0.0004435906,0.0008013392,0.002941018,0.0002532248,0.0009428769,0.0006554965,0.0004836601,0.0003892401],"category_scores_gemma":[0.001245521,0.0003612126,0.0001329775,0.001066004,0.00004025267,0.0008533173,0.00003161214,0.0004092475,0.00001033215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002292335,"about_ca_system_score_gemma":0.0002432701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005070384,"about_ca_topic_score_gemma":0.0009321256,"domain_scores_codex":[0.9928982,0.0003296043,0.001560936,0.001644004,0.003066274,0.000501014],"domain_scores_gemma":[0.996638,0.0009400764,0.0006594435,0.0004071109,0.001173588,0.0001817841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002745289,0.0009847566,0.004021525,0.0006795208,0.00009169296,0.000005223406,0.01049796,0.05386264,0.006996557,0.0004847045,0.001223676,0.9184064],"study_design_scores_gemma":[0.001500941,0.0001141609,0.06544163,0.0000583435,0.00007466727,0.00001303026,0.01043815,0.9112549,0.003042699,0.007286213,0.0002774952,0.0004977882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8749314,0.00009048755,0.1144433,0.00001141494,0.0002172258,0.002652143,0.00001867949,0.00005877636,0.007576616],"genre_scores_gemma":[0.9557647,0.000004171308,0.04047965,0.00005790499,0.0001417661,0.000311342,0.0006500704,0.00005517812,0.002535205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9179087,"threshold_uncertainty_score":0.999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.172620698526483,"score_gpt":0.5130553074011904,"score_spread":0.3404346088747074,"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."}}