{"id":"W3123677873","doi":"10.1557/opl.2012.1199","title":"Knowledge Diversity in the Emerging Global Bio-Nano Sector","year":2012,"lang":"en","type":"article","venue":"MRS Proceedings","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Multinational corporation; Diversity (politics); Nanotechnology; Knowledge base; Technological convergence; Business; Industrial organization; Biotechnology; Materials science; Engineering; Biology; Computer science; Political science; Telecommunications","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":[0.0006969005,0.00008666713,0.0001274584,0.0001220881,0.0002224744,0.00004104868,0.0002422592,0.00006778791,0.0001329373],"category_scores_gemma":[0.00006184379,0.00007747625,0.00004300598,0.0007421253,0.00003462121,0.0003741851,0.0001394654,0.0001010451,0.0005009174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001092616,"about_ca_system_score_gemma":0.000005653716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001757928,"about_ca_topic_score_gemma":0.000009295492,"domain_scores_codex":[0.9992823,0.000002399903,0.000230451,0.0001445427,0.0000278519,0.0003124377],"domain_scores_gemma":[0.9997487,0.000009372243,0.0001156387,0.00006385281,0.00002969261,0.00003271504],"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":[0.000002359207,0.00004422085,0.491504,0.00001216737,0.000004480502,7.915857e-8,0.004346781,1.035663e-7,0.000007675396,0.4974207,0.006527283,0.0001301571],"study_design_scores_gemma":[0.0004550551,0.00002505878,0.6776893,0.00001295447,0.000004201271,0.000006522987,0.001104743,0.0001074356,0.0001413718,0.03218233,0.2879978,0.000273301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7768087,0.0004266026,0.00003295946,0.001100914,0.0003435231,0.00008994,0.00002038715,0.00002338451,0.2211536],"genre_scores_gemma":[0.9982632,0.00001464585,0.00006653818,0.0008271142,0.000313626,0.000007786302,0.000002150924,0.000005402246,0.0004995802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4652384,"threshold_uncertainty_score":0.6438447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07827303620110879,"score_gpt":0.2659323553121125,"score_spread":0.1876593191110037,"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."}}