{"id":"W7096697848","doi":"","title":"Intangible Assets and Their Contribution to Productivity Growth in Ontario∗","year":2013,"lang":"en","type":"article","venue":"","topic":"Intellectual Capital and Performance Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Investment (military); Productivity; Capital (architecture); Fixed asset; Intangible asset; Business sector; Physical capital; Business operations; Fixed investment","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001774676,0.00009397716,0.0001284859,0.0002122571,0.00006357796,0.00017736,0.00006315641,0.00002906763,0.001640953],"category_scores_gemma":[0.00007299514,0.00006464915,0.00002558494,0.0003601905,0.00001393759,0.001272004,0.00009006426,0.00008586638,0.0008098284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004542838,"about_ca_system_score_gemma":0.000009076352,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1860843,"about_ca_topic_score_gemma":0.2114009,"domain_scores_codex":[0.999467,0.000003323586,0.0001147272,0.0001710654,0.00006541191,0.0001784825],"domain_scores_gemma":[0.9997199,0.00001276828,0.00002780951,0.00007360805,0.0001567791,0.000009161084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004111648,0.0001092087,0.9681463,0.00004099948,0.00002578064,0.000001085868,0.0005261754,0.0000173283,0.002342009,0.01541606,0.008309412,0.005024526],"study_design_scores_gemma":[0.0002935432,0.00003250644,0.959784,0.00002231043,0.00001413684,0.000001383073,0.0002829024,0.003656008,0.003296761,0.0144012,0.01791142,0.0003037729],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984314,0.00001198724,0.000198493,0.001340698,0.00005724856,0.0002269339,2.162759e-7,0.0000296401,0.01382081],"genre_scores_gemma":[0.9974079,0.000001511331,0.00002051534,0.001021515,0.0001330912,0.00003140456,0.00001220186,0.000004533978,0.001367333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02531662,"threshold_uncertainty_score":0.9999682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01057282215509271,"score_gpt":0.1878285022896137,"score_spread":0.177255680134521,"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."}}