{"id":"W2046671470","doi":"10.1108/17465660610667784","title":"Generalizability modeling of the foundations of customer delight","year":2006,"lang":"en","type":"article","venue":"Journal of Modelling in Management","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Generalizability theory; Customer satisfaction; Marketing; Variance (accounting); Originality; Structural equation modeling; Variation (astronomy); Customer retention; Sample (material); Computer science; Psychology; Econometrics; Service (business); Service quality; Business; Statistics; Mathematics; Social psychology; Machine learning","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":[0.001434226,0.0001185544,0.0002762151,0.0003658916,0.00007057382,0.00004315405,0.0004313407,0.00004432635,0.00003982381],"category_scores_gemma":[0.00001083964,0.00008880391,0.0002033218,0.0006192672,0.00004195669,0.0004651549,0.0001437834,0.0001559822,0.000005461646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005163563,"about_ca_system_score_gemma":0.0000181694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001690116,"about_ca_topic_score_gemma":0.0001892065,"domain_scores_codex":[0.9980794,0.00002555137,0.001113624,0.000125551,0.0004917252,0.0001641271],"domain_scores_gemma":[0.9985307,0.00002514878,0.0008029075,0.0002833058,0.0003512504,0.000006713352],"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":[0.00003136742,0.0002117553,0.004512562,0.0004430162,0.00003208589,0.000001796419,0.00006553259,0.9574248,0.00005198067,0.03673225,0.0002612053,0.0002316555],"study_design_scores_gemma":[0.0005391457,0.000004717621,0.001451048,0.0001947986,0.0001274562,8.10513e-7,0.0002694168,0.9697433,0.00004947305,0.02439181,0.003121484,0.0001065134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8411556,0.0001706678,0.1485416,0.0008363671,0.000370926,0.0002076298,0.000001181946,0.00000813721,0.008707918],"genre_scores_gemma":[0.9967705,0.00003783624,0.002665838,0.0001941916,0.0002152027,0.000002446459,0.000002044353,0.00001195026,0.00009997502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1556149,"threshold_uncertainty_score":0.3621318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03583020217003566,"score_gpt":0.2467984407903361,"score_spread":0.2109682386203004,"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."}}