{"id":"W7067737442","doi":"","title":"Neo-‐Colonial Criminology: Quantifying Silence","year":2014,"lang":"en","type":"article","venue":"Digital Scholarship - Texas Southern University (Texas Southern University)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Elite; Indigenous; Mainstream; Silence; Subject (documents); Criminal justice; State (computer science); Fourth World","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003836472,0.0005094913,0.0003836265,0.0003686377,0.0005263276,0.0002422206,0.001504464,0.0005888697,0.0001155405],"category_scores_gemma":[0.0003417883,0.0005985895,0.0003446584,0.0004381917,0.0004827557,0.0001348114,0.0008715435,0.0007267898,0.001376738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001627708,"about_ca_system_score_gemma":0.000142368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001679844,"about_ca_topic_score_gemma":0.0001400167,"domain_scores_codex":[0.9974028,0.0003183694,0.0002771911,0.0007999595,0.0003992396,0.0008024478],"domain_scores_gemma":[0.9980866,0.00009337383,0.0003434048,0.0008504518,0.0002350503,0.0003911736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002133732,0.0006186523,0.9553074,0.0002503415,0.0007739328,0.0003234137,0.004921376,0.001252959,0.006441837,0.01146581,0.0005203552,0.01599014],"study_design_scores_gemma":[0.006868969,0.001507792,0.02803265,0.0002369089,0.0004890296,0.0001347228,0.0236485,0.001469598,0.001734466,0.0007315309,0.9315684,0.003577375],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965475,0.00003568604,0.004695056,0.0001624918,0.0001671752,0.0002516916,0.0007294376,0.0002174335,0.02826609],"genre_scores_gemma":[0.9772434,0.00001669846,0.0008144621,0.0001823362,0.00017164,1.025941e-7,0.0004581307,0.00006583265,0.02104736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9310481,"threshold_uncertainty_score":0.9996465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02577093727458612,"score_gpt":0.2248476540987333,"score_spread":0.1990767168241472,"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."}}