{"id":"W1485144092","doi":"10.1007/978-3-642-13059-5_39","title":"A Semantic Model for Social Recommender Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Recommender system; Computer science; Information overload; Semantics (computer science); Information retrieval; 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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001513238,0.0006309571,0.0008241407,0.0007714135,0.0005430781,0.001041471,0.003692946,0.0006172664,0.000004165599],"category_scores_gemma":[0.00003804168,0.0005683894,0.0002624446,0.0003097185,0.0003302275,0.0005818216,0.001063398,0.001048637,0.00001125541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002690353,"about_ca_system_score_gemma":0.0005254931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004128182,"about_ca_topic_score_gemma":0.0001032519,"domain_scores_codex":[0.9959813,0.00003408065,0.0007536951,0.001645984,0.0007548576,0.0008300586],"domain_scores_gemma":[0.9973282,0.0003614693,0.0004638068,0.001331321,0.0003554637,0.0001597812],"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":[0.00001213073,0.00009571414,0.00001600377,0.0005020928,0.0000627245,0.00003849612,0.003193101,0.01051917,0.0005386878,0.343545,0.001591453,0.6398854],"study_design_scores_gemma":[0.0001932535,0.00007449955,0.000002451337,0.0001874875,0.000007472256,0.00005134197,1.400729e-7,0.7945696,0.0003214854,0.1986113,0.00540726,0.000573658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00000738119,0.0001988274,0.9902581,0.00173077,0.003545298,0.001167662,0.000015307,0.0004032009,0.002673485],"genre_scores_gemma":[0.1680628,0.00003001277,0.8271371,0.001579858,0.001416081,0.000174709,0.00001064372,0.0000988344,0.001490055],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7840504,"threshold_uncertainty_score":0.9999955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04398901412991223,"score_gpt":0.2810613700753398,"score_spread":0.2370723559454276,"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."}}