{"id":"W4390338679","doi":"10.3390/digital4010003","title":"Bias Reduction News Recommendation System","year":2023,"lang":"en","type":"article","venue":"Digital","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Recommender system; Computer science; Reduction (mathematics); Baseline (sea); Dual (grammatical number); Big data; Diversity (politics); Information retrieval; Artificial intelligence; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001750392,0.00007811772,0.00009266785,0.0001422069,0.00006988589,0.0005182817,0.0002539334,0.00003951515,0.000002545326],"category_scores_gemma":[0.00001430403,0.00007034342,0.00004953252,0.0004906508,0.000006660481,0.001164381,0.00008451679,0.00004763245,0.0004033145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005736597,"about_ca_system_score_gemma":0.00001569296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003106179,"about_ca_topic_score_gemma":0.000001145907,"domain_scores_codex":[0.9992856,0.00002540846,0.0001914926,0.0002295001,0.0001116365,0.0001563848],"domain_scores_gemma":[0.9995489,0.00002351517,0.00007357979,0.0002741326,0.00003435465,0.0000455707],"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":[0.00000164666,0.00002337492,0.0008350223,0.00003778239,0.00001598696,0.000009662607,0.0004258488,0.000003886782,0.000182727,0.05861151,0.1224261,0.8174264],"study_design_scores_gemma":[0.0006183165,0.0003115574,0.002817901,0.000228704,0.000006860128,0.0005298805,0.002590587,0.04505968,0.01000979,0.009017528,0.9278775,0.0009316522],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04190864,0.00002102706,0.7332849,0.005692992,0.004470742,0.0005555694,0.00002132202,0.008915352,0.2051294],"genre_scores_gemma":[0.9977204,0.00000457054,0.001112192,0.00002311668,0.0001383427,0.00002832987,0.00004519886,0.000008311442,0.0009195178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9558118,"threshold_uncertainty_score":0.5183927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05868565952940198,"score_gpt":0.2652049638498676,"score_spread":0.2065193043204656,"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."}}