{"id":"W4321788223","doi":"10.3390/s23052495","title":"Hybrid Recommendation Network Model with a Synthesis of Social Matrix Factorization and Link Probability Functions","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"","keywords":"Recommender system; Matrix decomposition; Computer science; Collaborative filtering; Bayesian network; Social network (sociolinguistics); Domain (mathematical analysis); Information retrieval; Cold start (automotive); Machine learning; Artificial intelligence; Social media; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003118119,0.00008147282,0.0001400896,0.00006943222,0.0001387879,0.00004482127,0.00009697712,0.00003983726,0.00000288521],"category_scores_gemma":[0.0000228251,0.00006832494,0.00002843797,0.0003182975,0.00002268999,0.0001660073,0.00006134066,0.00005785603,0.000003093521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000250843,"about_ca_system_score_gemma":0.00002540623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002293178,"about_ca_topic_score_gemma":0.00001128504,"domain_scores_codex":[0.9992719,0.00008158408,0.0001857323,0.0002197827,0.0001040003,0.000137048],"domain_scores_gemma":[0.9995324,0.0000896963,0.0001136691,0.0001637403,0.00007237919,0.00002811387],"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":[0.0001966421,0.0003015473,0.03061038,0.001016389,0.0004209807,0.00001041507,0.008412342,0.09685072,0.001021557,0.1593371,0.04252084,0.659301],"study_design_scores_gemma":[0.0001428867,0.0001069295,0.005032224,0.00004125646,0.00001757785,0.000007335769,0.00005769858,0.973321,0.001623817,0.01720612,0.002243229,0.0001998837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1637366,0.000004180922,0.8312503,0.003094627,0.0001441466,0.0003379944,0.00001794639,0.000491019,0.0009232636],"genre_scores_gemma":[0.9816265,0.000009116848,0.01805469,0.000011816,0.00007008639,0.0000321344,0.00001161053,0.000008172948,0.0001759254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8764703,"threshold_uncertainty_score":0.278621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581018177965112,"score_gpt":0.2532821163960565,"score_spread":0.2274719346164054,"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."}}