{"id":"W6637570","doi":"10.26481/dis.20130517rb","title":"Impacts of government incentives to R&amp;D, innovation and productivity : a microeconometric analysis of the Québec case","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Government; Université de Sherbrooke","keywords":"Favourite; Feeling; Incentive; Productivity; Government (linguistics); Media studies; Political science; Sociology; Engineering; Psychology; Law; Economics; Social psychology; Economic growth; Market economy; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001643726,0.0002973413,0.0006777169,0.00285772,0.002255208,0.00410206,0.001354744,0.001342357,0.01175911],"category_scores_gemma":[0.00750582,0.0002681419,0.0008442815,0.007965649,0.001500091,0.0009868531,0.001118635,0.001665325,0.0006734732],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05616153,"about_ca_system_score_gemma":0.01930399,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9909356,"about_ca_topic_score_gemma":0.9903721,"domain_scores_codex":[0.9978361,0.0005357511,0.00006189744,0.0001369798,0.0004179662,0.001011397],"domain_scores_gemma":[0.9916046,0.003422669,0.001113581,0.0003579918,0.002095853,0.001405355],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006942924,0.0007011967,0.7693048,0.0003161102,0.0007137941,0.002972197,0.002194231,0.06313179,0.0007727488,0.07803509,0.05152188,0.02964193],"study_design_scores_gemma":[0.0001191143,0.0001147576,0.8788806,0.0002435839,0.0002667326,0.0002245479,0.006902057,0.08670404,0.0003235131,0.003494925,0.02259384,0.0001322646],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309565,0.003400573,0.0007521472,0.009826274,0.00004730192,0.0001384858,0.008383151,0.00005835962,0.04643722],"genre_scores_gemma":[0.9888038,0.0006750634,0.0001783166,0.0002876325,0.00002163967,0.00003649586,0.001201522,0.000009752498,0.008785767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9983563,"threshold_uncertainty_score":0.4074823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02542127618072922,"score_gpt":0.2553765040068932,"score_spread":0.229955227826164,"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."}}