{"id":"W2901333361","doi":"10.5267/j.msl.2018.11.002","title":"Experiencing the AI emergence in Indian retail – Early adopters approach","year":2018,"lang":"en","type":"article","venue":"Management Science Letters","topic":"AI in Service Interactions","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Early adopter; Marketing; Computer science; Advertising","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001031066,0.0001717177,0.0001050668,0.0004971178,0.0006910365,0.0006426926,0.004494596,0.00002375832,0.00005718897],"category_scores_gemma":[0.00002126298,0.0001351176,0.00004631619,0.003387785,0.0008440351,0.002599319,0.00112097,0.0002378765,0.0002080127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001615388,"about_ca_system_score_gemma":0.00001731787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002617111,"about_ca_topic_score_gemma":0.00005685665,"domain_scores_codex":[0.9972969,0.00006375679,0.0002894117,0.0008070602,0.0008400698,0.0007027891],"domain_scores_gemma":[0.9984721,0.00002883282,0.0001039412,0.001261413,0.00003799834,0.00009570843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004194547,0.0005801896,0.1146107,0.0001620178,0.0001212284,0.0006888993,0.4310451,0.00727639,0.03379172,0.1817377,0.03774581,0.1921983],"study_design_scores_gemma":[0.001428015,0.0004176657,0.4920755,0.0003443727,0.00004081812,0.0001403298,0.05083985,0.3777827,0.01065126,0.002459717,0.06091765,0.002902173],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5984855,0.000007190758,0.346003,0.03151236,0.001572869,0.0004967514,3.013674e-7,0.0001688991,0.02175315],"genre_scores_gemma":[0.9562675,0.00000260411,0.02139481,0.02196401,0.00008370161,0.00008985882,2.69708e-7,0.000007631387,0.0001895777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3802052,"threshold_uncertainty_score":0.8352152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631594597116651,"score_gpt":0.2547542249966185,"score_spread":0.238438279025452,"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."}}