{"id":"W1967541337","doi":"10.5539/res.v5n4p135","title":"Determines of Sectoral R&amp;D Investment in the UK: A Dymanic Panel Approach","year":2013,"lang":"en","type":"article","venue":"Review of European Studies","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Investment (military); Estimation; Economics; Affect (linguistics); Panel data; Econometrics; R&D intensity; Random effects model; Fixed effects model; Scale (ratio); Meta-analysis; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001138425,0.0002600022,0.0006116553,0.001583922,0.0002421693,0.0008738755,0.0004757341,0.0005454065,0.004610747],"category_scores_gemma":[0.002866941,0.0003572922,0.0007091641,0.002897605,0.0001690117,0.0004500776,0.0008730789,0.0004636238,0.001244595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001045581,"about_ca_system_score_gemma":0.0007598918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0837822,"about_ca_topic_score_gemma":0.07935479,"domain_scores_codex":[0.9988078,0.0005396419,0.0001130091,0.0002351149,0.0001334298,0.0001709659],"domain_scores_gemma":[0.9964108,0.001571999,0.001136777,0.0002873128,0.0004383607,0.0001548561],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005621829,0.0003164452,0.8786573,0.0005580958,0.001405729,0.001221068,0.0008876662,0.05128729,0.001458568,0.007503192,0.01273508,0.04340729],"study_design_scores_gemma":[0.00006005565,0.0002361886,0.9301408,0.0001434019,0.0004939716,0.0002617498,0.0009934754,0.04272889,0.001157162,0.001760356,0.02196588,0.00005807541],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9591261,0.002940517,0.009937904,0.0008041062,0.00003471379,0.00008475687,0.02119865,0.00004893735,0.005824366],"genre_scores_gemma":[0.9665678,0.001863449,0.003039802,0.0001815518,0.00003545148,0.0001257007,0.02037853,0.00001076102,0.007797016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9988616,"threshold_uncertainty_score":0.1665891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2067840056040094,"score_gpt":0.276811880730489,"score_spread":0.0700278751264796,"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."}}