{"id":"W2162670686","doi":"","title":"Learning Fair Representations","year":2013,"lang":"en","type":"article","venue":"","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1001,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"ENCODE; Metric (unit); Computer science; Representation (politics); Group (periodic table); Population; Artificial intelligence; Machine learning; Transfer of learning","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000308284,0.00002507403,0.00003702414,0.00001763412,0.000733413,0.0002289347,0.00008204833,0.00005557287,0.003600381],"category_scores_gemma":[0.001121195,0.00002301686,0.0000266479,0.0001083098,0.0001281835,0.0004525816,0.00001587653,0.0001291412,0.0007138271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000179072,"about_ca_system_score_gemma":0.00006957243,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03883117,"about_ca_topic_score_gemma":0.002420334,"domain_scores_codex":[0.9994647,0.00009359434,0.00005738707,0.00006465004,0.0001704624,0.0001491992],"domain_scores_gemma":[0.9995044,0.0001605415,0.00001926047,0.00004739528,0.000175506,0.00009292863],"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":[3.550905e-7,0.00002263677,0.01427829,0.000001411619,0.00001037842,6.769541e-7,0.07414655,0.00001915552,0.0003183859,0.8651791,0.03336805,0.01265505],"study_design_scores_gemma":[0.0001808333,0.00005713678,0.05130145,0.000007756395,0.000007612811,1.727156e-7,0.2448202,0.0001414719,0.000152369,0.377256,0.3258147,0.0002602826],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09558013,0.000005867562,0.0001162893,0.03975783,0.00008296544,0.00008549044,8.026787e-8,0.0001026967,0.8642687],"genre_scores_gemma":[0.9193852,0.00004362282,0.0004211521,0.0006010763,0.000134459,0.000006286813,6.410514e-7,0.00000285319,0.07940471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8238051,"threshold_uncertainty_score":0.9973105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04779731958860933,"score_gpt":0.4055875139673011,"score_spread":0.3577901943786918,"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."}}