{"id":"W2143334947","doi":"10.1002/meet.14504701330","title":"A comparison between usage‐based and citation‐based methods for recommending scholarly research articles","year":2010,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Recommender system; Citation; Computer science; Collaborative filtering; Information retrieval; Digital library; World Wide Web; Usage data","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":[0.00821809,0.00009298697,0.000228237,0.0005756498,0.001201391,0.0005486151,0.001121918,0.00007755031,1.676742e-7],"category_scores_gemma":[0.001398431,0.00007025572,0.00007099176,0.003467659,0.00166559,0.003197045,0.0003573087,0.0003040116,1.442497e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004539837,"about_ca_system_score_gemma":0.0001410454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001679779,"about_ca_topic_score_gemma":7.951448e-7,"domain_scores_codex":[0.9987097,0.000009848623,0.000364158,0.0002262327,0.0003469956,0.000343044],"domain_scores_gemma":[0.9967509,0.0005011783,0.0005111795,0.0001934629,0.001977735,0.00006556058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007890367,0.00002347161,0.03387152,0.0001404602,0.00001643665,2.096651e-9,0.002761173,3.483345e-7,0.09441238,0.1415136,0.001579344,0.7256734],"study_design_scores_gemma":[0.0009083961,0.0009128929,0.008392375,0.00007858317,0.00002373057,0.000005177259,0.008178359,0.2589,0.5899641,0.06187407,0.0704194,0.0003429336],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4757023,0.00001100273,0.5063928,0.01672818,0.00006493539,0.0008008776,0.00000581994,0.0001502439,0.0001438199],"genre_scores_gemma":[0.5478898,0.000002760405,0.4517533,0.0002194287,0.000007356169,0.000123203,3.28108e-7,0.000002287986,0.000001514444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7253304,"threshold_uncertainty_score":0.9240248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1124896791338546,"score_gpt":0.4429243135539227,"score_spread":0.3304346344200682,"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."}}