{"id":"W3170772624","doi":"","title":"Research Guides: Government Documents and Information Canada: Resources, Tools and Calculators","year":2019,"lang":"en","type":"libguides","venue":"","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Computer science; World Wide Web; Business; Information retrieval; Data science; Political 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":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003116316,0.001461915,0.001481052,0.01219046,0.006665839,0.0127236,0.002561404,0.003260357,0.5770069],"category_scores_gemma":[0.01619867,0.001689238,0.0006589153,0.02465426,0.002123905,0.005433072,0.002013057,0.003319363,0.4091401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03541984,"about_ca_system_score_gemma":0.1453694,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8887636,"about_ca_topic_score_gemma":0.9290094,"domain_scores_codex":[0.9951543,0.0001853414,0.0002261801,0.0002708181,0.003740119,0.0004231993],"domain_scores_gemma":[0.9723272,0.00204545,0.0004187637,0.001015797,0.02230199,0.001890766],"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":[0.00001744318,0.00002698468,0.0001261711,0.0001362776,0.00000137818,0.0000079598,0.00004917451,0.0000787577,0.00006749409,0.004280737,0.9537904,0.04141727],"study_design_scores_gemma":[0.000009501209,0.000006305216,0.001056338,0.000162463,0.000003985621,0.00001346465,0.0001657955,0.0001725451,0.0002489357,0.001150108,0.9969931,0.0000175296],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0009150015,0.003273084,0.002066862,0.007050357,0.001456391,0.0004981433,0.0977778,0.008078557,0.8788838],"genre_scores_gemma":[0.001437989,0.001518301,0.001883478,0.0003562546,0.00005966668,0.00007016728,0.01294999,0.001129318,0.9805949],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9872764,"threshold_uncertainty_score":0.6033484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02546916836702251,"score_gpt":0.2579631847032515,"score_spread":0.232494016336229,"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."}}