{"id":"W7029733485","doi":"","title":"Maher Arar's Story &amp; Acceptance Speech at the Institute for Policy Studies 30th Annual Letelier-Moffitt Awards","year":2006,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Aging and Gerontology Research","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Public policy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003236448,0.000742487,0.0007950856,0.0009324588,0.007540097,0.006849488,0.00161719,0.01191003,0.3030369],"category_scores_gemma":[0.008799856,0.0004683807,0.000414232,0.00117044,0.001093622,0.00242241,0.002541148,0.007925725,0.1774065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004395822,"about_ca_system_score_gemma":0.005744922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04165563,"about_ca_topic_score_gemma":0.1051671,"domain_scores_codex":[0.9969196,0.000378332,0.00006606545,0.0002236579,0.00177033,0.0006420254],"domain_scores_gemma":[0.9947345,0.000890194,0.0001953391,0.0002194285,0.001908351,0.002052289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002648244,0.000008000116,0.00001860833,0.00000478285,2.112034e-7,0.00001678726,0.0000272057,0.000002551053,0.00001173278,0.0005720355,0.9979147,0.001420629],"study_design_scores_gemma":[0.000004058473,0.000006120455,0.000394883,0.00002616578,8.695299e-7,0.00001814164,0.0002512922,0.00001015587,0.00003011947,0.0001625889,0.9990884,0.000007121694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0008318041,0.003874647,0.0001102971,0.3426687,0.01755501,0.00009381471,0.001081113,0.0003219692,0.6334627],"genre_scores_gemma":[0.002013644,0.0008815958,0.00006112412,0.02097577,0.001232163,0.00004648606,0.0001271491,0.00008021507,0.9745817],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3030369,"threshold_uncertainty_score":0.9941332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316929278736248,"score_gpt":0.3038384643421643,"score_spread":0.2806691715548019,"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."}}