{"id":"W7135957046","doi":"","title":"Algorithmic discrimination in Europe: Challenges and Opportunities for EU equality law","year":2020,"lang":"en","type":"other","venue":"Research at the University of Copenhagen (University of Copenhagen)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for International Governance Innovation","funders":"","keywords":"European union; Legislation; Government (linguistics); Work (physics); Inequality","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":[0.009181084,0.000298223,0.0006073044,0.001139556,0.004066892,0.01299772,0.001454826,0.008260676,0.01474184],"category_scores_gemma":[0.01353817,0.0002142002,0.0006554411,0.001987982,0.01080358,0.01133881,0.008092176,0.005516636,0.001648821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003642294,"about_ca_system_score_gemma":0.004951756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005483114,"about_ca_topic_score_gemma":0.004330054,"domain_scores_codex":[0.995123,0.002410999,0.0001951675,0.000559139,0.0008727013,0.0008390109],"domain_scores_gemma":[0.9969205,0.001568178,0.0001629749,0.0005473856,0.000399262,0.0004018024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007782752,0.00001189114,0.0001318999,0.0000176825,0.000003983583,0.00002627228,0.0004191843,0.0003276738,0.00002818445,0.9717811,0.01107358,0.01617067],"study_design_scores_gemma":[0.000006353642,0.00000805397,0.0003803164,0.0001792085,0.000003934895,0.00004915639,0.001168938,0.0006528546,0.00009966503,0.8555721,0.1418665,0.00001296132],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02902273,0.02547051,0.02723365,0.2088191,0.002727675,0.00003503399,0.0002310366,0.0001632915,0.706297],"genre_scores_gemma":[0.8557711,0.009316659,0.01872233,0.05131884,0.001556817,0.0001080588,0.0004407688,0.0002510431,0.06251443],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01474184,"threshold_uncertainty_score":0.04931635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2531013088350381,"score_gpt":0.3268707186694786,"score_spread":0.07376940983444058,"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."}}