{"id":"W3094599270","doi":"","title":"LibGuides: Government Publications - Canada: Google Canadian Government Documents","year":2009,"lang":"en","type":"libguides","venue":"","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); World Wide Web; Library science; Political science; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001040914,0.0003512947,0.0004649773,0.00009290824,0.001132872,0.0004389534,0.0009991999,0.0002797811,0.008296721],"category_scores_gemma":[0.0006793913,0.0003455269,0.0002188284,0.0007052441,0.0001047745,0.0002420007,0.0000895322,0.0003250816,0.00007035028],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01252219,"about_ca_system_score_gemma":0.01358572,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.998843,"about_ca_topic_score_gemma":0.9999278,"domain_scores_codex":[0.9937313,0.0003349034,0.0006408796,0.0006027379,0.003884159,0.0008060394],"domain_scores_gemma":[0.9976178,0.0003950514,0.0003402742,0.000446885,0.0002246993,0.0009753139],"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":[0.000001739285,0.00003277001,0.0005688404,0.000006132518,0.000141694,0.000007408835,0.0001987268,0.00002496395,1.41771e-7,0.03641611,0.9347445,0.02785699],"study_design_scores_gemma":[0.0000866198,0.00001651256,0.003108962,0.00002860447,0.000103168,4.942491e-7,0.0009283615,0.00004928932,0.00000318696,0.002626792,0.9926465,0.0004015006],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00006778875,0.0005275849,0.0003164842,0.0464573,0.001192947,0.0004243595,0.0007219275,0.00007875412,0.9502128],"genre_scores_gemma":[0.009117087,0.0006656692,0.004908858,0.00853326,0.0016092,0.00007359626,0.0004409286,0.00003914158,0.9746122],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05790203,"threshold_uncertainty_score":0.9998997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641126571406805,"score_gpt":0.3118988430651922,"score_spread":0.2854875773511242,"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."}}