{"id":"W4221063232","doi":"10.2139/ssrn.4019672","title":"Case Study: The Distilling of a Biased Algorithmic Decision System through a Business Lens","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Lens (geology); Computer science; Artificial intelligence; Optics; Physics","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":[0.009012265,0.0005245861,0.0004323711,0.001947907,0.004324132,0.006047344,0.001972508,0.004269909,0.007304226],"category_scores_gemma":[0.04255519,0.0002727965,0.0004994208,0.001995274,0.004653681,0.003919765,0.003699306,0.003280419,0.000859844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002598725,"about_ca_system_score_gemma":0.002955815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006726627,"about_ca_topic_score_gemma":0.007322584,"domain_scores_codex":[0.9890286,0.008283881,0.0002513074,0.000463415,0.001511393,0.000461392],"domain_scores_gemma":[0.9657928,0.02730942,0.001060522,0.002593031,0.001990524,0.001253697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.001472131,0.001706687,0.03142848,0.0004856145,0.0001666664,0.01174481,0.04909771,0.03820286,0.006214602,0.7048075,0.01596488,0.138708],"study_design_scores_gemma":[0.0004902268,0.001438626,0.01253018,0.0005938923,0.0001668607,0.006086708,0.07287263,0.3254724,0.02036174,0.4049046,0.154781,0.0003010599],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7241194,0.0005089202,0.169568,0.01979228,0.0002497205,0.0004770489,0.0003833918,0.000347064,0.08455412],"genre_scores_gemma":[0.9420846,0.0001418057,0.05255449,0.0006488726,0.00004134782,0.00008837109,0.00009299489,0.00006292512,0.00428472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009012265,"threshold_uncertainty_score":0.04766202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06206970607792436,"score_gpt":0.2865725862476688,"score_spread":0.2245028801697445,"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."}}