{"id":"W2949236029","doi":"10.35295/osls.iisl/0000-0000-0000-1047","title":"The battle of numbers","year":2019,"lang":"en","type":"article","venue":"Oñati Socio-legal Series","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Racialization; Bureaucracy; Refugee; Political science; Politics; Racism; Public administration; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003602915,0.00006893627,0.0001045469,0.00001354425,0.0005747246,0.00009834363,0.0001800074,0.0000773572,0.0007583501],"category_scores_gemma":[0.0003671923,0.00004814026,0.00007002927,0.0001278236,0.0003548838,0.0005360134,0.00001450905,0.00007675902,0.0001530332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006941563,"about_ca_system_score_gemma":0.000224302,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003063892,"about_ca_topic_score_gemma":0.02118923,"domain_scores_codex":[0.9991167,0.0001320516,0.0001695049,0.0001038729,0.0003039592,0.0001739794],"domain_scores_gemma":[0.9993081,0.0002742204,0.0001047694,0.0001417705,0.0001331726,0.00003797526],"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":[0.00002385474,0.00001901681,0.01688656,0.00001581307,0.00002170841,1.437243e-7,0.05102308,0.000003177673,0.0007288678,0.8993024,0.03038528,0.00159012],"study_design_scores_gemma":[0.00008481528,0.00005360644,0.003210127,0.00001162712,0.000006197914,2.223259e-7,0.03354644,0.000005775735,0.001081155,0.003109439,0.958809,0.00008164694],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7921398,0.0002579782,0.00003442256,0.003743809,0.001334991,0.0002227988,0.000008757278,0.00005290837,0.2022045],"genre_scores_gemma":[0.9487457,0.0004028519,0.0001298079,0.00005679256,0.0001904846,0.0000103117,0.000008848672,0.000007106126,0.05044806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9284236,"threshold_uncertainty_score":0.9966715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00564730376727348,"score_gpt":0.2610701561352023,"score_spread":0.2554228523679289,"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."}}