{"id":"W6939193938","doi":"10.6068/dp14ba8c2a1e036","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Science and Technology - Innovation | Country: Canada | Table: Survey of innovation, logging and manufacturing industries, percentage of innovative plants, by type of co-operative arrangements and geographic location of cooperation partners | Variable: Plants with co-operative arrangements, Paper manufacturing, Cooperation with competitors or other firms in sector | Units: %, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-181.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competitor analysis; Economic statistics; Census; Summary statistics; Official statistics; Business statistics; Publication; Statistical analysis; Statistician","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":[0.002366832,0.002600771,0.002975503,0.01068045,0.003913134,0.005688687,0.005415625,0.001638042,0.09896085],"category_scores_gemma":[0.02124495,0.001888818,0.002035248,0.05906515,0.0007546692,0.002650739,0.00234698,0.003248106,0.06003281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06879999,"about_ca_system_score_gemma":0.1673019,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953707,"about_ca_topic_score_gemma":0.9931264,"domain_scores_codex":[0.9937636,0.0003217228,0.0006956605,0.0006524806,0.003148115,0.001418503],"domain_scores_gemma":[0.9478911,0.00182399,0.001416995,0.001136722,0.04560125,0.002129989],"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":[0.00001861689,0.000008046156,0.0009217106,0.0002321092,0.00001417701,0.000005774695,0.00002128162,0.00008998921,0.000007693189,0.0002755685,0.9970518,0.001353085],"study_design_scores_gemma":[0.0001592954,0.00001437612,0.03319794,0.0008460747,0.00007648391,0.00002418289,0.0006649893,0.0003608685,0.0001841861,0.0005145434,0.9638683,0.00008880627],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000516556,0.00004664666,0.00001653686,0.000107039,0.00002242295,0.00001355706,0.9987894,0.000045054,0.0009077723],"genre_scores_gemma":[0.0007999087,0.0002935686,0.0003462364,0.0001731371,0.0000183611,0.0001229236,0.9930348,0.00009127332,0.005119699],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09896085,"threshold_uncertainty_score":0.4991812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03848120943571244,"score_gpt":0.2847806582211267,"score_spread":0.2462994487854143,"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."}}