{"id":"W4412377968","doi":"10.1145/3726302.3730328","title":"Extending MovieLens-32M to Provide New Evaluation Objectives","year":2025,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Universitas Brawijaya","keywords":"MovieLens; Computer science; Information retrieval; Recommender system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01379651,0.002494693,0.001919666,0.003560812,0.0008800165,0.002688861,0.001780535,0.001528893,0.002874587],"category_scores_gemma":[0.04029804,0.0005694881,0.001229268,0.00376021,0.0004291015,0.00377656,0.002653645,0.002177107,0.002601956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001950726,"about_ca_system_score_gemma":0.001749082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009166023,"about_ca_topic_score_gemma":0.02211506,"domain_scores_codex":[0.9877563,0.004286308,0.001560845,0.001819815,0.004057603,0.0005190084],"domain_scores_gemma":[0.9759169,0.006981067,0.001878504,0.007463933,0.006546549,0.001212982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003100062,0.002039289,0.06463204,0.002122581,0.0008489185,0.0002916458,0.0006754041,0.05690575,0.009231835,0.01005819,0.3355592,0.5145351],"study_design_scores_gemma":[0.0009625404,0.001972863,0.06904873,0.0003318786,0.000198009,0.0005560399,0.0003295396,0.6770824,0.01528063,0.01859933,0.2152686,0.0003693778],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3334194,0.005703994,0.2784292,0.00385194,0.001587031,0.003494515,0.2837015,0.04672071,0.0430917],"genre_scores_gemma":[0.3669474,0.0005858503,0.3675065,0.0009512858,0.0004370722,0.00303117,0.2490536,0.001645116,0.009842044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01379651,"threshold_uncertainty_score":0.07296377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02881643056604848,"score_gpt":0.3381081247072179,"score_spread":0.3092916941411694,"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."}}