{"id":"W2975269869","doi":"10.18280/mmep.060307","title":"A Personalized Collaborative Filtering Recommendation Algorithm Based on Linear Regression","year":2019,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Xinjiang","keywords":"Collaborative filtering; Computer science; Linear regression; Regression; Algorithm; Recommender system; Data mining; Artificial intelligence; Machine learning; Mathematics; Statistics","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":[0.000376861,0.0001752382,0.0002409112,0.0001078385,0.00005651873,0.0001235125,0.0001592243,0.0000774764,0.00001765653],"category_scores_gemma":[0.00001141818,0.0001369291,0.00004092972,0.0001744415,0.00000805744,0.0001816675,0.00005556627,0.000156482,0.00001923252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003012204,"about_ca_system_score_gemma":0.00001194212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003236922,"about_ca_topic_score_gemma":3.012278e-8,"domain_scores_codex":[0.99906,0.00002888955,0.0002415093,0.0003075135,0.000159689,0.0002024259],"domain_scores_gemma":[0.999427,0.0001466908,0.00006053337,0.0002441291,0.00004414143,0.00007748977],"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":[0.00001506735,0.0002242164,0.00001589513,0.001501156,0.00005163423,0.000005872542,0.003148406,0.8607258,0.001760375,0.08281429,0.0002268123,0.04951047],"study_design_scores_gemma":[0.0002492215,0.0001121645,6.960705e-7,0.0006465482,0.000002604188,0.000004921967,0.00001157434,0.9927551,0.0007562731,0.002910306,0.002377736,0.0001728804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001249726,0.00003693895,0.9966936,0.0004297143,0.0001133685,0.0003056061,0.000002183129,0.0003426924,0.0008261998],"genre_scores_gemma":[0.1768614,0.00002090361,0.8227877,0.00005733361,0.00003010136,0.00006657983,0.000005466282,0.00002240587,0.0001480488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1756117,"threshold_uncertainty_score":0.5583806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02190382097099392,"score_gpt":0.2353951800954297,"score_spread":0.2134913591244358,"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."}}