{"id":"W4232792048","doi":"10.1515/iupac.66.0001","title":"Biochemical Engineering in Biotechnology","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bioprocess; Biotechnology; Bioprocess engineering; Biochemical engineering; Industrial biotechnology; Engineering; Process (computing); Metabolic engineering; Chemistry; Computer science; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001678673,0.0003250394,0.0003647452,0.0004811531,0.00001490165,0.00001476443,0.000283835,0.000909636,0.0006631663],"category_scores_gemma":[0.0001142634,0.0002747182,0.00007556337,0.0002650101,0.00006623638,0.0000465876,0.00009343471,0.0006742898,0.000005764743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004228176,"about_ca_system_score_gemma":0.00006097279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001568349,"about_ca_topic_score_gemma":0.00001844276,"domain_scores_codex":[0.9986947,0.000009614908,0.0003139178,0.0003431025,0.0002779982,0.0003607273],"domain_scores_gemma":[0.9993488,0.00001698316,0.00003559019,0.0004747515,0.00004602501,0.00007791378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001549997,0.00003205567,0.000001348011,0.0003566022,0.0000249752,0.00002335357,0.000001622164,0.00002470768,0.002611928,0.00000230606,0.9957011,0.001204497],"study_design_scores_gemma":[0.0005648886,0.00004229492,0.000005684406,0.0002193211,0.00001329695,0.00001702254,0.000003938354,0.0001765631,0.007860291,0.000008871836,0.9907411,0.0003466644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009787474,0.001096471,0.0001203613,0.0005700944,0.001057035,0.0001436174,0.9956553,0.0003700401,0.000008348781],"genre_scores_gemma":[0.0003681798,0.002999599,0.00007014037,0.00003883277,0.0005634961,0.00000810821,0.9958789,0.00004140519,0.00003128703],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005248363,"threshold_uncertainty_score":0.9999705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00679838833076612,"score_gpt":0.2973679026912721,"score_spread":0.290569514360506,"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."}}