{"id":"W4285059900","doi":"10.1561/1500000079","title":"Fairness in Information Access Systems","year":2022,"lang":"en","type":"article","venue":"Foundations and Trends® in Information Retrieval","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"Micron Foundation; National Science Foundation","keywords":"Computer science; Information access; Centrality; Personalization; Intersection (aeronautics); Information system; World Wide Web; Data science; Information retrieval; Knowledge management","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":[0.03125163,0.001029033,0.002384061,0.003420437,0.006225863,0.01663875,0.003305971,0.005481952,0.01258126],"category_scores_gemma":[0.07620551,0.0009184027,0.001901346,0.004126783,0.01452035,0.02469927,0.009124582,0.005980994,0.002234307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006382088,"about_ca_system_score_gemma":0.005346585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003473614,"about_ca_topic_score_gemma":0.001440881,"domain_scores_codex":[0.9564242,0.02003459,0.003617886,0.007233623,0.009607262,0.003082463],"domain_scores_gemma":[0.9359319,0.03838254,0.003563359,0.01435299,0.005919088,0.001850082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001507614,0.00001123986,0.0002267517,0.000032188,0.00001162358,0.00002458984,0.0001821708,0.001195555,0.00006349952,0.9926156,0.0007805131,0.00484123],"study_design_scores_gemma":[0.00001226357,0.00001427777,0.000118212,0.00003235933,0.000009351214,0.00004568225,0.00006601585,0.005837847,0.0001132917,0.9862881,0.007449742,0.0000128519],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.04146914,0.006999624,0.7743487,0.02052597,0.001096856,0.0005666614,0.0006783123,0.0005351414,0.1537795],"genre_scores_gemma":[0.826534,0.004445352,0.1281638,0.002989901,0.002615554,0.001070947,0.0004996692,0.0002640377,0.03341686],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.03125163,"threshold_uncertainty_score":0.1652763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04526192200601802,"score_gpt":0.3783950567943201,"score_spread":0.3331331347883021,"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."}}