{"id":"W3194347029","doi":"10.1007/s13278-021-00785-5","title":"Multi-source based movie recommendation with ratings and the side information","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"MovieLens; Computer science; Recommender system; Collaborative filtering; Variety (cybernetics); Information retrieval; Trailer; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006805584,0.00008056947,0.0002077512,0.00005235282,0.0004889321,0.0003838791,0.0000810878,0.00003890038,0.000003503227],"category_scores_gemma":[0.00001985789,0.00005412496,0.00005999432,0.0007191594,0.00003741208,0.0003407676,0.00007937353,0.00006949146,2.270315e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001014509,"about_ca_system_score_gemma":0.00002464396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001168718,"about_ca_topic_score_gemma":0.0003495605,"domain_scores_codex":[0.9992612,0.0001705102,0.0002064991,0.0001437764,0.00009228757,0.000125751],"domain_scores_gemma":[0.9994579,0.0001439838,0.0001844102,0.0001051984,0.00008050712,0.00002800417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000259904,0.00002263987,0.0291397,0.00002946713,0.0007317215,0.000002492747,0.01426676,0.001344627,0.00001385316,0.007781399,0.001874572,0.9447668],"study_design_scores_gemma":[0.001058435,0.00002480175,0.0116213,0.00002896322,0.0002547919,0.000004167358,0.001606929,0.9690689,0.00004373432,0.0002252181,0.01587695,0.0001858123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007960537,0.0001060859,0.9881495,0.003030147,0.00002950841,0.00007303841,5.355736e-7,0.00005115748,0.0005994381],"genre_scores_gemma":[0.8690384,0.00003540494,0.1294202,0.001310887,0.00008899852,0.00001955121,0.00002579227,0.000003516682,0.00005728767],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9677243,"threshold_uncertainty_score":0.376052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142841721809073,"score_gpt":0.232922560340746,"score_spread":0.2214941431226553,"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."}}