{"id":"W2766999628","doi":"10.1111/jems.12073","title":"Does Service Bundling Reduce Churn?","year":2014,"lang":"en","type":"article","venue":"Journal of Economics & Management Strategy","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Broadband; Triple play (telecommunications); Matching (statistics); Service (business); Panel data; Construct (python library); Business; Telecommunications; Computer science; Marketing; Econometrics; Computer network; Economics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002375366,0.0001741608,0.0006362943,0.0006064961,0.0007518091,0.001085184,0.0005085027,0.0007169446,0.004899065],"category_scores_gemma":[0.01520526,0.0002066286,0.0004436016,0.001037277,0.0006550739,0.001420551,0.0009398508,0.0005881313,0.000530768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001081979,"about_ca_system_score_gemma":0.001683072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01504554,"about_ca_topic_score_gemma":0.02221974,"domain_scores_codex":[0.9986221,0.0006335872,0.0000477936,0.0001391061,0.0002025762,0.0003549196],"domain_scores_gemma":[0.9906124,0.003903748,0.002785996,0.0007083244,0.0007396288,0.001249912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001725831,0.003473586,0.6189542,0.0003892459,0.0005297885,0.0002453637,0.002384357,0.01841556,0.005865586,0.01432042,0.007594485,0.3261015],"study_design_scores_gemma":[0.0002371868,0.00301908,0.9108648,0.0002006772,0.000420464,0.0002249517,0.005697306,0.04231318,0.002648017,0.01793361,0.01638959,0.00005110784],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940519,0.0005158533,0.001197962,0.0009991645,0.00002154989,0.00002478604,0.0001152452,0.00003538244,0.003038153],"genre_scores_gemma":[0.9981269,0.0001682595,0.0008102846,0.0001920156,0.00001905225,0.00001497734,0.0001144343,0.000007485794,0.000546526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01504554,"threshold_uncertainty_score":0.02991593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02032573875182596,"score_gpt":0.2069101374718758,"score_spread":0.1865843987200498,"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."}}