{"meta":{"query_hash":"7bf4b07509be","filters":{"venue":"IJTLS"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/7bf4b07509be","api":"https://metacan.xera.ac/api/v1/cohort?venue=IJTLS"},"results":[{"id":"W7135233160","doi":"10.65713/ijtlsv1i301","title":"ENHANCING CUSTOMER RETENTION THROUGH AI-ENABLED CRM SOLUTIONS A MARKETING ANALYTICS PAPER OF GENPACT","year":2025,"lang":"","type":"article","venue":"IJTLS","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SAIT Polytechnic","funders":"","keywords":"Customer retention; Customer intelligence; Customer relationship management; Customer advocacy; Analytics; Customer satisfaction; Predictive analytics; Market segmentation; Customer to customer; Service quality","score_opus":0.0257551432873806,"score_gpt":0.2720737399554815,"score_spread":0.2463185966681009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7135233160","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.095,0.02300801,0.038836703,0.670084,0.016760271,0.00037554043,0.0007019502,0.001308855,0.15392467],"genre_scores_gemma":[0.62065357,0.033666506,0.03715346,0.07489597,0.014661037,0.00038383988,0.0007109261,0.0010982251,0.21677646],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980716,0.0006212703,0.000041762152,0.00025157115,0.0008320099,0.00018183677],"domain_scores_gemma":[0.9941981,0.0036394612,0.00021351718,0.0002949548,0.0012030695,0.00045082034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048299944,0.000619683,0.00045926147,0.001468194,0.0017651654,0.006004839,0.0007002008,0.001404078,0.0055357236],"category_scores_gemma":[0.007233736,0.0002551959,0.00037639812,0.0020044518,0.0020430787,0.0049996222,0.0015920595,0.0041928184,0.0010773567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024568356,0.0002368883,0.00450036,0.000347355,0.00007470221,0.0003915229,0.0039044009,0.0039023182,0.0030220416,0.12911062,0.51261806,0.34164605],"study_design_scores_gemma":[0.00008590863,0.00039739473,0.0073097693,0.0005509782,0.00007358723,0.00039840981,0.003385852,0.027408637,0.0090766335,0.06466552,0.8864997,0.0001475734],"about_ca_topic_score_codex":0.004374475,"about_ca_topic_score_gemma":0.004413955,"teacher_disagreement_score":0.006004839,"about_ca_system_score_codex":0.0032271852,"about_ca_system_score_gemma":0.0028242252,"threshold_uncertainty_score":0.02554375},"labels":[],"label_agreement":null}]}