{"id":"W4390055400","doi":"10.18280/mmep.100613","title":"A Novel Context-Aware Deep Learning Algorithm for Enhanced Movie Recommendation Systems","year":2023,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Context (archaeology); Recommender system; Deep learning; Algorithm; Artificial intelligence; Machine learning; History","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":[0.0005213564,0.0001321669,0.00023128,0.0001297417,0.0001294679,0.0002227454,0.0001334282,0.00006976241,0.000001603281],"category_scores_gemma":[0.00004533793,0.0001207801,0.00005519863,0.0003061988,0.000006737067,0.0002021867,0.00005350724,0.0001057794,0.00001152029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002014167,"about_ca_system_score_gemma":0.000006235867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006961774,"about_ca_topic_score_gemma":3.354222e-7,"domain_scores_codex":[0.9990338,0.00001226747,0.00030889,0.0002757035,0.0001216772,0.000247639],"domain_scores_gemma":[0.9994509,0.0002125691,0.00006103842,0.0001289172,0.00007349443,0.00007310347],"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":[3.782616e-7,0.00001377361,4.373771e-7,0.0002233918,0.00002252445,2.063485e-7,0.0004856845,0.9398556,0.0004389698,0.01334553,0.000005686762,0.04560781],"study_design_scores_gemma":[0.0001928309,0.00003012201,6.843146e-7,0.0001413259,0.00001266271,0.000003271088,0.00005520651,0.9962577,0.0001081131,0.002613255,0.0004347746,0.0001501132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004317158,0.00006363509,0.9985893,0.0001301051,0.0001053263,0.0002285901,0.000002199657,0.0004128273,0.00003627034],"genre_scores_gemma":[0.681917,0.0001021496,0.3172005,0.00002019016,0.00007388293,0.0002496556,0.00006377223,0.00003617314,0.0003367002],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6814853,"threshold_uncertainty_score":0.4925271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02999672657664264,"score_gpt":0.2264188995902111,"score_spread":0.1964221730135685,"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."}}