{"id":"W4367310345","doi":"10.24143/2072-9502-2023-2-116-124","title":"Model and algorithm for supporting decision on selection of products for recommendation to user based on analysis of statistical implication","year":2023,"lang":"en","type":"article","venue":"VESTNIK OF ASTRAKHAN STATE TECHNICAL UNIVERSITY SERIES MANAGEMENT COMPUTER SCIENCE AND INFORMATICS","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Edgewood Chemical Biological Center; H2020 European Research Council; Réseau québécois de recherche sur la douleur","keywords":"Computer science; Association rule learning; Recommender system; Data mining; Ranking (information retrieval); Cluster analysis; Measure (data warehouse); Credibility; Inference; Set (abstract data type); Information retrieval; Quality (philosophy); Transparency (behavior); Filter (signal processing); Collaborative filtering; Rank (graph theory); Machine learning; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001336633,0.0008058068,0.001607008,0.001465128,0.0009061391,0.001922407,0.00229279,0.001851849,0.005854294],"category_scores_gemma":[0.003831317,0.0004278794,0.001033784,0.00137081,0.0005225475,0.001690721,0.001056746,0.001568726,0.001519254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001349056,"about_ca_system_score_gemma":0.002662632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009407985,"about_ca_topic_score_gemma":0.006236464,"domain_scores_codex":[0.9990089,0.0001950015,0.00008290813,0.0002613336,0.00032223,0.0001295911],"domain_scores_gemma":[0.9985061,0.0009379264,0.0001076472,0.00005715751,0.0003538829,0.00003723345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004265721,0.0003332754,0.004599924,0.0003085801,0.0001509237,0.0004919501,0.0002444235,0.6193607,0.002251957,0.03929303,0.008285871,0.3242527],"study_design_scores_gemma":[0.00003474825,0.00005371038,0.0002082155,0.00001631104,0.0000282429,0.00008234543,0.00002022009,0.9872515,0.0004708116,0.01056825,0.001256916,0.000008626473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01136189,0.0002953117,0.9828197,0.0006076891,0.00006257484,0.0002486157,0.0002541974,0.0007135563,0.003636405],"genre_scores_gemma":[0.2889371,0.0005668192,0.7010694,0.0003560021,0.0001052606,0.001172457,0.0009396606,0.00006902411,0.006784316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009407985,"threshold_uncertainty_score":0.0195846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169840876898509,"score_gpt":0.2713769939555745,"score_spread":0.2543929062657236,"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."}}