{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00118151,0.0009194429,0.001350423,0.001615746,0.0008507554,0.001418044,0.001424782,0.001245997,0.01214171],"category_scores_gemma":[0.004234637,0.0004144453,0.0008814327,0.001281111,0.0001989979,0.001714692,0.001209218,0.00120889,0.01787787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004715347,"about_ca_system_score_gemma":0.001141823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007970142,"about_ca_topic_score_gemma":0.01162769,"domain_scores_codex":[0.998996,0.0001106852,0.00009330884,0.0003405107,0.0003692745,0.00009022662],"domain_scores_gemma":[0.9980893,0.0002616721,0.0000895733,0.0005664652,0.0009037141,0.00008928298],"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":[0.0007346153,0.0003701459,0.007299419,0.0006942507,0.0003024998,0.0004502384,0.0002490292,0.009829897,0.04426496,0.005807017,0.09913969,0.8308583],"study_design_scores_gemma":[0.0003647186,0.0004833834,0.007886004,0.0001797904,0.0007454088,0.001525106,0.0002816906,0.6428558,0.1015189,0.0117807,0.2320977,0.0002809263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06298984,0.004383907,0.7922032,0.001351986,0.001137304,0.001495514,0.01233876,0.08084714,0.04325234],"genre_scores_gemma":[0.3365963,0.002255841,0.553262,0.001540276,0.0006479576,0.0006221295,0.02037508,0.001109136,0.08359116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01214171,"threshold_uncertainty_score":0.04061806,"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."}}