{"id":"W2023596549","doi":"10.1007/s00530-012-0298-5","title":"Folkommender: a group recommender system based on a graph-based ranking algorithm","year":2012,"lang":"en","type":"article","venue":"Multimedia Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Recommender system; Computer science; Popularity; Ranking (information retrieval); Graph; Information retrieval; Differential privacy; Theoretical computer science; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001005071,0.000803539,0.001571002,0.001480636,0.0008944703,0.001339696,0.001767179,0.001409205,0.008589805],"category_scores_gemma":[0.002894403,0.0003367478,0.0007446748,0.00165275,0.0002720604,0.002033052,0.001103727,0.000930528,0.004744067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004590564,"about_ca_system_score_gemma":0.0008027434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006484563,"about_ca_topic_score_gemma":0.01769501,"domain_scores_codex":[0.9994,0.0002077029,0.0000315836,0.0001438506,0.0001782838,0.00003868139],"domain_scores_gemma":[0.9991134,0.0002415405,0.00004101753,0.0002776686,0.0002501866,0.00007614717],"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":[0.001195875,0.001072875,0.003937704,0.0005703149,0.0006659672,0.0003301273,0.0002796386,0.06504942,0.01620046,0.01453067,0.07480287,0.821364],"study_design_scores_gemma":[0.0003712617,0.0004727264,0.001718112,0.00003416952,0.0002523864,0.0003265057,0.0001107112,0.9428221,0.009034678,0.01308999,0.0316592,0.0001081467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03198255,0.001141211,0.9449809,0.0006534348,0.0004313433,0.00042408,0.001401146,0.01250944,0.006475931],"genre_scores_gemma":[0.2228135,0.0005666309,0.7535371,0.0004197654,0.0001843367,0.0003009941,0.002725442,0.0005149799,0.0189373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008589805,"threshold_uncertainty_score":0.02873576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0244173518647893,"score_gpt":0.2456368146818819,"score_spread":0.2212194628170926,"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."}}