{"id":"W1944240654","doi":"10.2139/ssrn.1945951","title":"Rewarding Innovation: Improving Federal Tax Support for Business R&D in Canada","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Incentive; Productivity; Business; Tax incentive; Tax credit; Public economics; Economics; Market economy; Economic growth","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":[0.007197538,0.0003648545,0.000682378,0.003996435,0.008196581,0.006831362,0.00329308,0.003571992,0.009447654],"category_scores_gemma":[0.03704588,0.000489735,0.0006672773,0.003659942,0.002072237,0.001879388,0.003585903,0.002980109,0.0005708715],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1702166,"about_ca_system_score_gemma":0.5268185,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9917054,"about_ca_topic_score_gemma":0.9961843,"domain_scores_codex":[0.9858903,0.001375315,0.0004610076,0.0005852907,0.00521569,0.006472384],"domain_scores_gemma":[0.9476632,0.00673761,0.003058941,0.001241071,0.02114519,0.02015398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001144846,0.001340018,0.2655667,0.0009833797,0.0003541889,0.0010087,0.006833082,0.02211115,0.00386596,0.1188217,0.2665786,0.3113917],"study_design_scores_gemma":[0.0007096485,0.0006174315,0.6127542,0.0008342802,0.0005562987,0.0002300699,0.009228007,0.02343823,0.003975474,0.01142622,0.3359525,0.0002777008],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6949559,0.004218083,0.003369633,0.1740241,0.0009646541,0.001069057,0.004983697,0.0007600085,0.1156549],"genre_scores_gemma":[0.9492215,0.00161434,0.002427765,0.008137919,0.0001852068,0.0001298936,0.0008604841,0.00005592854,0.03736711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8297834,"threshold_uncertainty_score":0.9624312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02697566751985191,"score_gpt":0.2641075606999744,"score_spread":0.2371318931801225,"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."}}