{"id":"W4291163510","doi":"10.1016/j.heliyon.2022.e10168","title":"The triple helix in developed countries: when knowledge meets innovation?","year":2022,"lang":"en","type":"article","venue":"Heliyon","topic":"University-Industry-Government Innovation Models","field":"Business, Management and Accounting","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Narodowym Centrum Nauki","keywords":"Triple helix; Inefficiency; Data envelopment analysis; Milestone; Government (linguistics); Order (exchange); Index (typography); Helix (gastropod); Value (mathematics); Sample (material); Economics; Econometrics; Mathematics; Statistics; Computer science; Geography; Physics; Finance; Microeconomics; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00223048,0.0004341932,0.0008244877,0.002576995,0.0009186837,0.004678404,0.0004301485,0.001060619,0.002804883],"category_scores_gemma":[0.007398754,0.0002186386,0.0008217303,0.004898311,0.002686158,0.005453129,0.00304862,0.001086275,0.0002388492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777622,"about_ca_system_score_gemma":0.001660519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005788822,"about_ca_topic_score_gemma":0.003586273,"domain_scores_codex":[0.9982943,0.0006592537,0.00007822245,0.0002370662,0.0002736622,0.0004574677],"domain_scores_gemma":[0.9971926,0.001308608,0.0008171773,0.0002254958,0.0002460887,0.0002101354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003292175,0.0001854349,0.1194119,0.0004568298,0.0003230057,0.001622486,0.002806357,0.1010651,0.0008665788,0.6864595,0.002848424,0.08362526],"study_design_scores_gemma":[0.00009254863,0.0005895225,0.09128706,0.0006102358,0.000218981,0.000770961,0.01554983,0.07824189,0.001819303,0.7825015,0.02821441,0.0001038511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8760763,0.003456854,0.0265619,0.00524476,0.00006289142,0.00006965835,0.0004836853,0.00005619584,0.08798775],"genre_scores_gemma":[0.997451,0.0008512404,0.0009593781,0.0001193557,0.00001182138,0.00001855973,0.00006313664,0.00000375984,0.0005218416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9990813,"threshold_uncertainty_score":0.01289761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03239709837189576,"score_gpt":0.2431544244524093,"score_spread":0.2107573260805136,"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."}}