{"id":"W6938782108","doi":"10.6068/dp14ba89ae3ba36","title":"Trend 1999 - 2003. Statistics Canada. CANSIM: Information and Communications Technology - Television and Radio Industries | Country: Canada | Table: Federal government expenditures on culture, by culture activity | Variable: University and college libraries, Federal government operating expenditures | Units: $CAD x 1,000, 1999-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-129.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Census; Economic statistics; Official statistics; Publication; Cable television; Statistical analysis; Summary statistics","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":[0.0020921,0.002435748,0.002633711,0.008694387,0.003349553,0.004960548,0.004984748,0.001543978,0.08695605],"category_scores_gemma":[0.01704754,0.001681692,0.002085228,0.04266648,0.0006312476,0.002596678,0.002075396,0.003150657,0.05125113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05463667,"about_ca_system_score_gemma":0.1480608,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946631,"about_ca_topic_score_gemma":0.9923576,"domain_scores_codex":[0.9955176,0.0002683041,0.0004506659,0.000525077,0.002275793,0.0009626069],"domain_scores_gemma":[0.9655442,0.001087672,0.0009655845,0.0008870708,0.03004953,0.001465986],"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":[0.00002457071,0.000007501631,0.0009757715,0.0002379277,0.00002037584,0.00000737594,0.00001848996,0.0001188686,0.000009201769,0.0004121908,0.9963526,0.0018151],"study_design_scores_gemma":[0.0001288672,0.00001184069,0.02085,0.0007434921,0.00006631407,0.00002504941,0.0004128497,0.0004847177,0.0001691227,0.0006542066,0.9763822,0.00007133349],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000577313,0.00006265329,0.00002754433,0.0001572141,0.00003390409,0.00001582426,0.9984622,0.00005947035,0.00112348],"genre_scores_gemma":[0.001040955,0.0003887479,0.0004447336,0.0001974421,0.00002318251,0.0001245272,0.9921566,0.0001274672,0.005496304],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08695605,"threshold_uncertainty_score":0.3964186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01619091589933038,"score_gpt":0.2251648078938492,"score_spread":0.2089738919945188,"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."}}