{"id":"W7143908787","doi":"10.34382/00011478","title":"Canadian nikkei institutions and spaces","year":2016,"lang":"en","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"","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":[0.0009957511,0.0006219705,0.0005534297,0.01435926,0.01032691,0.01120918,0.001658572,0.0006516675,0.06788629],"category_scores_gemma":[0.00520876,0.0004670855,0.0005457438,0.03691127,0.001429091,0.002514404,0.002965282,0.001197994,0.007788934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0796131,"about_ca_system_score_gemma":0.125931,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9902132,"about_ca_topic_score_gemma":0.9953508,"domain_scores_codex":[0.9975157,0.00009955824,0.00009241026,0.0002434238,0.001328805,0.0007200687],"domain_scores_gemma":[0.9948716,0.0002764729,0.0004665847,0.0003570218,0.003237118,0.0007912733],"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":[0.0001769412,0.00004728179,0.03793136,0.0007990761,0.00006809888,0.0002497352,0.003823914,0.001279508,0.0003377213,0.2266736,0.5616437,0.166969],"study_design_scores_gemma":[0.000008926468,0.000007408323,0.05723931,0.0001903488,0.00003067714,0.00007788191,0.003962931,0.0003558865,0.0003574589,0.002509022,0.9351992,0.00006086582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04991575,0.007280191,0.001887424,0.006272578,0.0005022589,0.0002104268,0.1958688,0.0008369445,0.7372257],"genre_scores_gemma":[0.3459487,0.0129054,0.006992542,0.0006188157,0.00009762989,0.0002531979,0.1033792,0.0005305831,0.529274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0796131,"threshold_uncertainty_score":0.5776362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04844042255200005,"score_gpt":0.2969671097801113,"score_spread":0.2485266872281112,"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."}}