{"id":"W6901579019","doi":"10.6068/dp14ba8ebaed471","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Economic Accounts - Environmental and Resource Accounts | Country: Canada | Table: Survey of innovation, selected service industries, percentage of total revenues from the sale of products to the mining and/or forestry and/or forest products industries | Variable: Forestry and/or forest products industry, Satellite telecommunications, 25% to 49% of revenues, Innovative business units | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-058.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; National accounts; Revenue; Census; Summary statistics; Service (business); Economic data; Natural resource","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":[0.001973008,0.002317808,0.002672458,0.009851959,0.003478295,0.00525155,0.004762847,0.001562758,0.09216146],"category_scores_gemma":[0.01891878,0.001609486,0.001871585,0.05549834,0.0007183703,0.002400038,0.002023405,0.00316378,0.05704066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06138301,"about_ca_system_score_gemma":0.1378656,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946375,"about_ca_topic_score_gemma":0.9927502,"domain_scores_codex":[0.9953727,0.0002511691,0.0005223697,0.0005432111,0.002298953,0.001011631],"domain_scores_gemma":[0.9596092,0.001556605,0.001128443,0.001049986,0.035213,0.001442721],"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":[0.00001651068,0.000005893383,0.000702147,0.0001995371,0.00001414921,0.000005884246,0.00001630832,0.00009538944,0.000006745697,0.0002863765,0.9976044,0.001046639],"study_design_scores_gemma":[0.000129948,0.000008621606,0.02205982,0.0006756318,0.00005932111,0.00002122035,0.0004785772,0.0003866799,0.0001482918,0.000535541,0.9754179,0.00007847454],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003992457,0.00004034017,0.0000115745,0.00009112838,0.00001877345,0.000009237177,0.9990358,0.00003423597,0.0007190162],"genre_scores_gemma":[0.0007232159,0.0002510059,0.0002565812,0.0001280549,0.00001547479,0.00009158856,0.9950013,0.00006512172,0.003467739],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09216146,"threshold_uncertainty_score":0.445367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04916711047738914,"score_gpt":0.2542571505917162,"score_spread":0.2050900401143271,"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."}}