{"meta":{"query_hash":"f25269a2b7d9","filters":{"venue":"2006 IEEE International Conference on Service Operations and Logistics, and Informatics"},"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/f25269a2b7d9","api":"https://metacan.xera.ac/api/v1/cohort?venue=2006+IEEE+International+Conference+on+Service+Operations+and+Logistics%2C+and+Informatics"},"results":[{"id":"W2039786694","doi":"10.1109/soli.2006.329026","title":"A Purchasing Sequences Data Mining Method for Customer Segmentation","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Service Operations and Logistics, and Informatics","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Purchasing; Market segmentation; Computer science; Segmentation; Data mining; Customer base; Product (mathematics); Artificial intelligence; Machine learning; Business; Marketing; Mathematics","score_opus":0.12357786249197945,"score_gpt":0.3485582641360812,"score_spread":0.22498040164410177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039786694","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.074614935,0.00004620847,0.85739595,0.005427522,0.0012944092,0.0008681182,0.0005734507,0.0001151713,0.059664235],"genre_scores_gemma":[0.8478928,0.00012797817,0.13683467,0.008599065,0.0013086966,0.000057545803,0.0044381986,0.00002329424,0.0007177086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990427,0.000007677868,0.00042710765,0.00017229708,0.00020594125,0.000144297],"domain_scores_gemma":[0.99915266,0.000060413764,0.00016073983,0.0001469237,0.00046457766,0.000014672102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031881555,0.00014903212,0.00013556039,0.00020331837,0.00031274714,0.0010139592,0.00020841317,0.000055521352,0.00006892334],"category_scores_gemma":[0.000046323064,0.00013512309,0.000016075635,0.00011935488,0.00004827647,0.0017566575,0.00007763572,0.00006928456,0.0000265515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017325515,0.00027966523,0.0036952582,0.0007625431,0.00015707458,0.0000032592861,0.00221544,0.033594046,0.0037827964,0.8449163,0.016408097,0.09401231],"study_design_scores_gemma":[0.0005950293,0.000016065256,0.00043360586,0.00005171586,0.00005015345,0.000004720897,0.0040418357,0.98300505,0.000064112275,0.001465823,0.010073078,0.00019879141],"about_ca_topic_score_codex":0.0014319929,"about_ca_topic_score_gemma":0.0019476283,"teacher_disagreement_score":0.94941103,"about_ca_system_score_codex":0.000023647512,"about_ca_system_score_gemma":0.00004142674,"threshold_uncertainty_score":0.9777632},"labels":[],"label_agreement":null}]}