{"id":"W4245466630","doi":"10.32920/ryerson.14644728","title":"Personalized recommender system on whom to follow in Twitter","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Recommender system; Computer science; Learning to rank; World Wide Web; Information retrieval; Social media; Graph; Rank (graph theory); Ranking (information retrieval); Theoretical computer science","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":[0.0008048584,0.0004390379,0.0007851782,0.0004482082,0.00007617666,0.001201241,0.00161782,0.0003690816,0.00006705799],"category_scores_gemma":[0.00001798507,0.0003804695,0.000292766,0.0003635467,0.00001200204,0.0001523422,0.002170543,0.0006615251,0.00007663347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005154859,"about_ca_system_score_gemma":0.0002016038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001190661,"about_ca_topic_score_gemma":0.0002527379,"domain_scores_codex":[0.9967723,0.0003854072,0.000639543,0.001295399,0.0004547282,0.000452614],"domain_scores_gemma":[0.9977062,0.0001034426,0.000162226,0.001741798,0.0001087951,0.0001775905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008656745,0.001052744,0.006317479,0.00302107,0.0006502093,0.001621137,0.03550098,0.0003350085,0.000324632,0.2602395,0.6065514,0.08429924],"study_design_scores_gemma":[0.008527649,0.001737455,0.01253798,0.03550306,0.000116395,0.0006180029,0.01483193,0.1202129,0.0157955,0.01168077,0.7655917,0.01284662],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01207262,0.0001690359,0.9010881,0.01183783,0.003455185,0.001342069,0.000004328712,0.00107346,0.06895734],"genre_scores_gemma":[0.8666279,0.00001636642,0.1226379,0.005358096,0.000190134,0.0006965488,0.00001620631,0.00004551252,0.004411329],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8545552,"threshold_uncertainty_score":0.9998647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06002510961448582,"score_gpt":0.2936494518470041,"score_spread":0.2336243422325183,"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."}}