{"id":"W1777585515","doi":"10.5267/j.msl.2015.8.003","title":"Design of an operations manager selection system in service encounter","year":2015,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chulalongkorn University","keywords":"Selection (genetic algorithm); Computer science; Service (business); Business; Process management; Operations management; Operations research; Knowledge management; Marketing; Artificial intelligence; Mathematics; Engineering","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":[0.006072742,0.0006517566,0.0009016619,0.003365331,0.002088169,0.003330592,0.001066738,0.0007887821,0.008155007],"category_scores_gemma":[0.009183899,0.0005259234,0.0004339509,0.002072721,0.0004658195,0.001615694,0.001376767,0.0007072041,0.001697635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001564404,"about_ca_system_score_gemma":0.003534771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002350932,"about_ca_topic_score_gemma":0.002153903,"domain_scores_codex":[0.9961002,0.001662848,0.0004163898,0.0006774319,0.0008515761,0.0002914552],"domain_scores_gemma":[0.9947072,0.002173058,0.0006036369,0.0001996967,0.001782543,0.0005337102],"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":[0.002343955,0.001542602,0.04139226,0.001001852,0.00021009,0.00132942,0.006898741,0.09730338,0.03873289,0.0260158,0.01576115,0.7674679],"study_design_scores_gemma":[0.0005719367,0.00158385,0.01736975,0.0001886932,0.0001898159,0.0004732126,0.00409715,0.9041764,0.02868555,0.007742231,0.03472171,0.0001997753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08743014,0.00009337952,0.8976293,0.0004823042,0.00007924208,0.003569101,0.0002983054,0.003776457,0.00664181],"genre_scores_gemma":[0.367018,0.00007507303,0.6262469,0.000108761,0.00005269811,0.00230981,0.0005347938,0.00008432724,0.003569693],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008155007,"threshold_uncertainty_score":0.03211612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794057878671758,"score_gpt":0.2248751156091521,"score_spread":0.2069345368224345,"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."}}