{"id":"W3012983490","doi":"","title":"Competing in Artificial Intelligence Chips: China’s Challenge amid Technology War","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Economic and Technological Innovation","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for International Governance Innovation","funders":"","keywords":"China; Frontier; Applications of artificial intelligence; Engineering; International trade; Business; Political science; Artificial intelligence; Computer science; Law","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001132885,0.0001536268,0.0003609333,0.000400319,0.0001169162,0.00003093803,0.0004451813,0.0002159793,0.0001261265],"category_scores_gemma":[0.0002601436,0.0001708279,0.00007429051,0.0006666423,0.00008240282,0.0001805461,0.00008397557,0.002356685,0.0003994237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005089754,"about_ca_system_score_gemma":0.0001150237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003291943,"about_ca_topic_score_gemma":0.0001622899,"domain_scores_codex":[0.9974451,0.00001281325,0.0008828157,0.0003587151,0.00002738538,0.001273149],"domain_scores_gemma":[0.9993613,0.0000166485,0.0004139798,0.000140973,0.00001966055,0.00004745447],"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":[0.00001383637,0.00005530567,0.004919656,0.000004214037,0.00002419925,0.000003706248,0.0001897326,0.00008139393,0.00002986215,0.9597247,0.000003220274,0.03495014],"study_design_scores_gemma":[0.0001352112,0.0002954584,0.0005302553,0.000009474998,0.000001615357,0.00002954615,0.002184336,0.003908026,0.0001358018,0.991659,0.0009168576,0.000194381],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8925808,0.006282328,0.05011579,0.04307628,0.0001890873,0.0001762187,0.00000628641,0.000149349,0.007423825],"genre_scores_gemma":[0.9959948,0.003194561,0.0003500197,0.0002159027,0.0001914056,0.000007828668,0.000003084278,0.00001877879,0.00002358697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.103414,"threshold_uncertainty_score":0.9999449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05032892460117461,"score_gpt":0.2350564007714061,"score_spread":0.1847274761702315,"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."}}