{"id":"W2889700901","doi":"10.4324/9781315751023-15","title":"Not so short and sweet: immigration detention in Canada","year":2015,"lang":"en","type":"article","venue":"","topic":"European Criminal Justice and Data Protection","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration detention; Immigration; Political science; Geography; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003077813,0.0003693589,0.000808837,0.001879199,0.02200554,0.008190818,0.00384838,0.007349579,0.006935925],"category_scores_gemma":[0.01542276,0.0006741892,0.000758141,0.005398939,0.004124719,0.002100148,0.006185074,0.01060807,0.0004341775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.120988,"about_ca_system_score_gemma":0.3294972,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996534,"about_ca_topic_score_gemma":0.9992505,"domain_scores_codex":[0.9905787,0.0007454659,0.0002411008,0.0003907236,0.001268866,0.006775143],"domain_scores_gemma":[0.9853071,0.001501385,0.001235063,0.0002221463,0.003629328,0.008104926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.001197367,0.001338023,0.5742016,0.0005927007,0.0004241652,0.008740664,0.06942576,0.003046013,0.0008288254,0.03909869,0.2036339,0.0974723],"study_design_scores_gemma":[0.0001482182,0.0002033512,0.640728,0.0009228879,0.0002514827,0.0008982918,0.2865616,0.002148482,0.000369023,0.003531804,0.06392247,0.0003143612],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8732058,0.004075869,0.000228459,0.09543926,0.0007503647,0.0001782912,0.001467138,0.00003264777,0.02462216],"genre_scores_gemma":[0.9688785,0.002102996,0.0002207784,0.01074961,0.0001371502,0.00004434993,0.0004870813,0.0000379521,0.01734169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.120988,"threshold_uncertainty_score":0.8778332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06187490033173328,"score_gpt":0.2947867027608462,"score_spread":0.2329118024291129,"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."}}