{"id":"W4400949440","doi":"10.5206/ijoh.2023.3.17541","title":"How Waitlist Management Biases Data Production in Built for Zero Communities","year":2024,"lang":"en","type":"article","venue":"International Journal on Homelessness","topic":"Homelessness and Social Issues","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Discretion; Process (computing); Process management; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001204054,0.0001910519,0.0003742291,0.0005827413,0.0004770106,0.0004386752,0.001195897,0.0001214028,0.00009763941],"category_scores_gemma":[0.0001908362,0.0001602335,0.00008240962,0.0002427244,0.00006424628,0.000807264,0.0003217657,0.0007580618,0.00004159678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004071275,"about_ca_system_score_gemma":0.0001416757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003131406,"about_ca_topic_score_gemma":0.004843595,"domain_scores_codex":[0.9979488,0.0002945303,0.0005108615,0.0002845934,0.0005946003,0.0003665881],"domain_scores_gemma":[0.9982864,0.0006714516,0.0001726927,0.000390513,0.0003997812,0.00007919702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001232547,0.001138452,0.03578273,0.002203856,0.00145534,0.001001383,0.08256971,0.0007329635,0.0001335191,0.1784717,0.01016806,0.6851097],"study_design_scores_gemma":[0.002756252,0.0001811727,0.01885072,0.009966252,0.0001138837,0.00001440133,0.4867307,0.003416569,0.0002267743,0.02652558,0.4504087,0.0008090559],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9695595,0.001351687,0.002623838,0.008624275,0.01496989,0.0007711403,0.0003765243,0.000138631,0.00158452],"genre_scores_gemma":[0.9920009,0.002244148,0.0002051153,0.0001233546,0.002254008,0.0001754917,0.0003709583,0.00004836415,0.002577709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6843007,"threshold_uncertainty_score":0.6534131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2128864251024003,"score_gpt":0.472501767833337,"score_spread":0.2596153427309367,"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."}}