{"id":"W6976896667","doi":"10.6068/dp14ba8cabbf390","title":"Trend 2000 - 2007. Statistics Canada. CANSIM: Information and Communications Technology - Business and Government Internet Use | Country: Canada | Table: Survey of electronic commerce and technology, use of information and communication technologies, by North American Industry Classification System (NAICS) | Variable: Enterprises that are presently using it, Clothing and clothing accessories stores, Internet | Units: %, 2000-2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-125.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business statistics; Official statistics; The Internet; Economic statistics; Government (linguistics); Descriptive statistics; Census; Information and Communications Technology; Information technology; Landline","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":[0.001930358,0.002488224,0.002727477,0.009837944,0.003360454,0.004855843,0.005242379,0.001463058,0.0635934],"category_scores_gemma":[0.01708816,0.001622421,0.002105713,0.04671979,0.0006537149,0.002623529,0.002438019,0.003298614,0.04510994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04635714,"about_ca_system_score_gemma":0.1311127,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9933326,"about_ca_topic_score_gemma":0.9919264,"domain_scores_codex":[0.9956003,0.0002455215,0.0004628653,0.0005197716,0.002175185,0.0009963106],"domain_scores_gemma":[0.9615616,0.00118992,0.00117178,0.0008978054,0.03359782,0.001581082],"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":[0.00002055376,0.000007885927,0.001244736,0.0002320374,0.0000202384,0.000006204818,0.00002071425,0.00009384596,0.000007446165,0.0002918734,0.9967403,0.001314244],"study_design_scores_gemma":[0.0001612371,0.00001616876,0.03684195,0.0009356564,0.00008683553,0.00002862401,0.0007366301,0.0005623772,0.000207484,0.0005923106,0.9597365,0.00009427381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000636925,0.0000424534,0.00001829665,0.0001032752,0.00002517736,0.00001317467,0.9990801,0.00004223618,0.0006115403],"genre_scores_gemma":[0.0006453673,0.0001968274,0.000224139,0.0001052312,0.00001621356,0.00009326196,0.9958096,0.00005891216,0.00285056],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0635934,"threshold_uncertainty_score":0.3363461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04406278398255876,"score_gpt":0.2596023562274169,"score_spread":0.2155395722448581,"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."}}