{"id":"W6920079125","doi":"10.6068/dp14baa3e0dce70","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Information and Communications Technology - Information and Communications Technology Sector | Country: Canada | Province: Prince Edward Island | Table: Survey of innovation, logging and manufacturing industries, percentage of innovative plants | Variable: Both product and process innovators, Food manufacturing and beverage and tobacco product manufacturing, All plants | Units: %, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-127.","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; Census; Official statistics; Product (mathematics); Summary statistics; Information and Communications Technology; Information technology; Business statistics; Publication","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":[0.002618068,0.002498253,0.002747686,0.009002395,0.004038331,0.005197451,0.00508719,0.001650973,0.1039198],"category_scores_gemma":[0.02381855,0.001807521,0.002106322,0.04877753,0.0007086509,0.002609351,0.002284547,0.003292825,0.06204704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06059494,"about_ca_system_score_gemma":0.1559078,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947397,"about_ca_topic_score_gemma":0.9927062,"domain_scores_codex":[0.9942153,0.000332638,0.0006714169,0.0006272933,0.002880461,0.001272811],"domain_scores_gemma":[0.9504758,0.001885271,0.001233334,0.001216995,0.04317841,0.002010295],"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":[0.00001709169,0.000006787774,0.0007664014,0.0002237527,0.00001349535,0.000005466257,0.00001857143,0.00008473409,0.000007140959,0.0002650594,0.9973231,0.001268546],"study_design_scores_gemma":[0.0001665365,0.00001355388,0.02785764,0.0008716221,0.00007179388,0.00002316471,0.0005703672,0.0003419553,0.00016639,0.0005276519,0.9693068,0.00008256312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004534876,0.00004749781,0.00001761465,0.0001128063,0.00002632976,0.00001379385,0.9988101,0.00004112298,0.0008854342],"genre_scores_gemma":[0.0007730715,0.0003025999,0.0003807206,0.000186192,0.00001961688,0.000129102,0.993224,0.00009002155,0.004894569],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1039198,"threshold_uncertainty_score":0.4396491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0302085403932623,"score_gpt":0.2582238106245332,"score_spread":0.2280152702312709,"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."}}