{"id":"W4295064625","doi":"10.1016/j.jik.2022.100263","title":"An institutional view on the leverage of external patent law expertise and patenting performance: Insights from China","year":2022,"lang":"en","type":"article","venue":"Journal of Innovation & Knowledge","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Fundamental Research Funds for the Central Universities; National University's Basic Research Foundation of China; National Natural Science Foundation of China","keywords":"Intellectual property; Patent law; Leverage (statistics); China; Business; Investment (military); Patent troll; Industrial organization; Law and economics; Economics; Law; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006000374,0.0001162903,0.0001749634,0.0002687986,0.0006117107,0.00009744169,0.0002423709,0.00002749664,0.0005296296],"category_scores_gemma":[0.00007390132,0.00007331341,0.0000414447,0.0006136063,0.00006485466,0.0008934871,0.0001236009,0.0003304921,0.00001598156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000509198,"about_ca_system_score_gemma":0.00004580066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008595416,"about_ca_topic_score_gemma":0.000005014811,"domain_scores_codex":[0.9987594,0.00004782467,0.0006347933,0.0001106208,0.0003427096,0.0001046076],"domain_scores_gemma":[0.9986764,0.00003030792,0.0006203479,0.0001039258,0.000560732,0.000008352476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002995844,0.003797602,0.04671861,0.0006537446,0.0003509106,0.00008951189,0.01407477,0.004447049,0.1799452,0.5168809,0.004654008,0.2253918],"study_design_scores_gemma":[0.009686138,0.001897417,0.5040702,0.003500087,0.0002996509,0.0001594035,0.004499563,0.2100171,0.03515458,0.02290467,0.2060162,0.001795027],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935355,0.0003831663,0.0004439237,0.0001647846,0.0007783059,0.000105243,0.000002609999,0.000007950709,0.00457853],"genre_scores_gemma":[0.9983814,0.00002465963,0.00004030921,0.0008131915,0.0006595306,0.000006449639,0.00001480091,0.00001032208,0.0000493307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4939763,"threshold_uncertainty_score":0.5799073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1415997625739344,"score_gpt":0.2422271021854767,"score_spread":0.1006273396115423,"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."}}