{"id":"W4240958360","doi":"10.1287/mksc.2013.0799","title":"Focus on Authors","year":2013,"lang":"en","type":"article","venue":"Marketing Science","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Focus (optics); Computer science; Marketing; Industrial organization; Business","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001468945,0.00007403333,0.00005514069,0.0002453151,0.0003448879,0.0006693835,0.0002681206,0.00001617679,0.0008126662],"category_scores_gemma":[0.0005322188,0.00006209572,0.00002229663,0.0008108512,0.0001217684,0.001191649,0.00009431267,0.00006578756,0.002189989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003192416,"about_ca_system_score_gemma":0.00001354806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003110951,"about_ca_topic_score_gemma":0.000007705864,"domain_scores_codex":[0.999018,0.000008296125,0.0001114229,0.0002371999,0.0003685113,0.000256638],"domain_scores_gemma":[0.9996157,0.00005381357,0.00007506984,0.0001432586,0.00009827886,0.00001386454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006612235,0.0001560632,0.1062164,0.0001093418,0.000006959263,0.000007977214,0.0002212679,0.0001057562,0.06476293,0.03727301,0.06419754,0.7268766],"study_design_scores_gemma":[0.0003492007,0.00001079439,0.9554623,0.00008137601,0.000009100317,0.000001476552,0.0005679497,0.02225419,0.00111777,0.00501449,0.01477183,0.0003595598],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7226885,0.000003704424,0.00005719429,0.001783821,0.000397097,0.0001208463,8.125562e-8,0.00009183407,0.2748569],"genre_scores_gemma":[0.9970191,4.925794e-7,0.0002268285,0.001389237,0.0002701663,0.00001207473,7.330596e-7,0.000006423767,0.001075004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8492458,"threshold_uncertainty_score":0.9985869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352268943069054,"score_gpt":0.2296666154630257,"score_spread":0.2161439260323351,"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."}}