{"id":"W6992494494","doi":"","title":"Linking R&amp;D, Innovation and Productivity in Canada, Sector Level Analysis","year":2016,"lang":"en","type":"other","venue":"uO Research (University of Ottawa)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation, Science and Economic Development Canada","funders":"","keywords":"Productivity; Process (computing); Estimation; Multifactor productivity; Production (economics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001592511,0.00028396,0.0005052629,0.002597718,0.001277051,0.002189891,0.0009494071,0.0004346572,0.00455814],"category_scores_gemma":[0.00805123,0.0002720145,0.0008174061,0.007990099,0.0008304525,0.0006814896,0.001986525,0.0008037772,0.0005112189],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02328579,"about_ca_system_score_gemma":0.04857289,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9924387,"about_ca_topic_score_gemma":0.9923034,"domain_scores_codex":[0.9984422,0.0002062904,0.00009445436,0.0002456552,0.0005649643,0.0004463485],"domain_scores_gemma":[0.9948952,0.001286248,0.0007921899,0.0003054042,0.002200935,0.0005200583],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007275344,0.00004934867,0.9437318,0.000108873,0.0002571558,0.0001381289,0.0007618183,0.02125185,0.0003318316,0.008194858,0.004194398,0.02090702],"study_design_scores_gemma":[0.0000228087,0.00004760237,0.9535873,0.0000666769,0.0001740618,0.00004755118,0.00201907,0.03017069,0.0006054594,0.002330843,0.01089319,0.00003481554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9390907,0.00148409,0.008430174,0.002276526,0.0000269036,0.0001785708,0.0291597,0.00027089,0.0190825],"genre_scores_gemma":[0.9798695,0.0005746689,0.005043897,0.0001235795,0.000007021417,0.00005564002,0.007459882,0.00002046476,0.00684541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9984075,"threshold_uncertainty_score":0.168951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1200124714750684,"score_gpt":0.31943835876784,"score_spread":0.1994258872927716,"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."}}