{"id":"W2348977701","doi":"","title":"Summary and analysis of patents related to cellulosic ethanol","year":2008,"lang":"en","type":"article","venue":"Xiandai huagong","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cellulosic ethanol; China; Index (typography); Business; Patent analysis; Agricultural economics; Political science; Engineering; Economics; Data science; Computer science; World Wide Web; Cellulose; Law; Chemical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008394197,0.00008072495,0.000152769,0.0001201655,0.00003625589,0.000003191647,0.00005263664,0.0000821253,0.00001188185],"category_scores_gemma":[0.00002910811,0.00007516913,0.00006618544,0.00033217,0.00003433875,0.000001839252,0.00003888969,0.0000416271,0.000002669797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003153846,"about_ca_system_score_gemma":0.000009923915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002652757,"about_ca_topic_score_gemma":0.000002875951,"domain_scores_codex":[0.999455,0.00001845562,0.0001473513,0.0002125316,0.00005784327,0.0001087624],"domain_scores_gemma":[0.9996854,0.000001422182,0.00003592382,0.0001812038,0.00004186117,0.00005417424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001966306,0.00001925392,0.009378011,0.000008423823,0.0002209285,0.000001337767,0.0001153582,0.0003788452,0.9880986,0.000004614762,0.0004071841,0.001347753],"study_design_scores_gemma":[0.0002240717,0.00009165415,0.07615001,0.00001041092,0.0001893019,0.00001320058,0.00001430389,0.00007981298,0.9167634,0.000002383687,0.006316008,0.0001454416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984801,0.00078981,0.0002473793,0.00005210439,0.0001144996,0.00006908544,0.00001930385,0.000009926632,0.0002177343],"genre_scores_gemma":[0.9975972,0.0004233849,0.0003277281,0.00003343148,0.00004194194,0.000002798644,0.0001001057,0.000008565442,0.001464915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07133523,"threshold_uncertainty_score":0.3065308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007789783011279612,"score_gpt":0.2144387410475522,"score_spread":0.2066489580362726,"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."}}