{"id":"W2388666479","doi":"","title":"Optimization of corn porous starch production based response surface design","year":2009,"lang":"en","type":"article","venue":"Food Science and Technology International","topic":"Enzyme Production and Characterization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Hydrolysis; Response surface methodology; Chemistry; Starch; Chromatography; Enzymatic hydrolysis; Absorption (acoustics); Porosity; Absorption of water; Corn starch; Chemical engineering; Food science; Materials science; Biochemistry; Organic chemistry; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001095394,0.0008856383,0.00086501,0.0003649209,0.0001389297,0.0005715564,0.0005702119,0.0005510466,0.0006882279],"category_scores_gemma":[0.001144583,0.000369677,0.0007088056,0.0004880164,0.0002360703,0.0002231796,0.0003541763,0.0004808721,0.000280336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003401252,"about_ca_system_score_gemma":0.0003173732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005256585,"about_ca_topic_score_gemma":0.0005788239,"domain_scores_codex":[0.9992421,0.0001969143,0.00005324077,0.0001225607,0.0003019211,0.00008324729],"domain_scores_gemma":[0.9996487,0.0001481649,0.00004823461,0.00002188899,0.000115531,0.00001749126],"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":[0.000309265,0.0002068261,0.0003929927,0.000307028,0.00003829027,0.00008745059,0.00003894804,0.03523124,0.931661,0.000503683,0.0001916984,0.03103165],"study_design_scores_gemma":[0.00008566115,0.000939742,0.001096225,0.000009745493,0.00003844091,0.00007842281,0.00002418759,0.1694189,0.8254949,0.0002300234,0.002547699,0.00003599207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3742099,0.0008123526,0.6201742,0.0001270456,0.00006144318,0.0005893674,0.0003169913,0.001114028,0.002594608],"genre_scores_gemma":[0.6500682,0.0007104977,0.3453655,0.00006523386,0.00001487617,0.001044082,0.0005493344,0.0001227461,0.002059489],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001095394,"threshold_uncertainty_score":0.005793095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336984575937458,"score_gpt":0.2550255414428104,"score_spread":0.2416556956834358,"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."}}