{"id":"W4401859670","doi":"10.2307/j.ctvxkn57g.12","title":"AGAINST REPRESENTATION","year":2018,"lang":"en","type":"book-chapter","venue":"Semiotics","topic":"Legal case studies and regulations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Representation (politics); Computer science; Political science","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":[0.0001591784,0.0001080256,0.000148652,0.00004426097,0.0005952303,0.00004466156,0.00010955,0.000238064,0.0009101008],"category_scores_gemma":[0.00009679379,0.0001020214,0.0001031208,0.00003411671,0.0004591695,0.00004793564,0.00005627885,0.0001327931,0.0004215962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001119681,"about_ca_system_score_gemma":0.0001217149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009774623,"about_ca_topic_score_gemma":0.001146355,"domain_scores_codex":[0.9991575,0.00001903218,0.0001603063,0.0001828356,0.0003195223,0.0001607311],"domain_scores_gemma":[0.9993448,0.00007407308,0.0001167786,0.0002005503,0.000195049,0.00006876713],"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":[0.000002486628,0.000005714759,0.00002564252,0.00001026869,0.0000644607,0.0000118807,0.006978591,0.000007385289,0.000001799312,0.6711726,0.3175984,0.00412083],"study_design_scores_gemma":[0.00003994134,0.00001010461,0.0000178841,0.00004219552,0.00003544789,2.549958e-7,0.000505282,0.000009924952,0.000002441619,0.03004458,0.969164,0.0001280087],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005307487,0.0002148281,0.00003892117,0.001684478,0.000965553,0.0001612086,0.00002097946,0.00006525979,0.9967957],"genre_scores_gemma":[0.002565523,0.001235914,0.0002825845,0.0002725797,0.002712532,9.008358e-7,0.00004239269,0.00002188093,0.9928657],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6515656,"threshold_uncertainty_score":0.9964965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04527262391891976,"score_gpt":0.3286682588917849,"score_spread":0.2833956349728651,"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."}}