{"id":"W3183305561","doi":"","title":"Mount A Libraries: Canadian Govt. & Politics: Government & Party Finance — Primary Sources","year":2019,"lang":"en","type":"article","venue":"","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Politics; Government (linguistics); Political science; Public administration; Library science; Business; Law; Computer science","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":[0.0006626801,0.0007806702,0.0005676727,0.008257528,0.0146131,0.007642108,0.001528656,0.001822216,0.1537908],"category_scores_gemma":[0.003936423,0.0006285069,0.0003866063,0.0245552,0.001259357,0.00186985,0.001851653,0.002114639,0.01697295],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1077962,"about_ca_system_score_gemma":0.2071186,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953036,"about_ca_topic_score_gemma":0.9981754,"domain_scores_codex":[0.9982353,0.00004891341,0.00004309066,0.0001015718,0.0009910394,0.0005800078],"domain_scores_gemma":[0.9954053,0.0002162601,0.0001709982,0.0001067616,0.003358631,0.0007420586],"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":[0.00002752048,0.00001045919,0.002305463,0.0002215974,0.000008541667,0.00009665827,0.0007510594,0.00006888389,0.00009689344,0.0236133,0.9394201,0.03337955],"study_design_scores_gemma":[0.00000470681,0.00000227981,0.01522699,0.0001377765,0.000008338926,0.00003289791,0.001108479,0.00005279741,0.0001615434,0.0006592345,0.9825842,0.00002082889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008877523,0.01177847,0.000405287,0.03843138,0.001450886,0.000134004,0.1211975,0.0005645688,0.8171604],"genre_scores_gemma":[0.05993715,0.007886806,0.0007499112,0.002466301,0.0003027485,0.0000644145,0.01748035,0.0002601575,0.9108522],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8922038,"threshold_uncertainty_score":0.7821196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004967132959923547,"score_gpt":0.1758200272585867,"score_spread":0.1708528942986632,"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."}}