{"id":"W4386929169","doi":"10.3390/pr11092801","title":"Special Issue on “Secondary Metabolites: Extraction, Optimization, Identification and Applications in Food, Nutraceutical, and Pharmaceutical Industries”","year":2023,"lang":"en","type":"article","venue":"Processes","topic":"Natural Antidiabetic Agents Studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Nutraceutical; Identification (biology); Extraction (chemistry); Biochemical engineering; Biotechnology; Business; Food science; Chemistry; Engineering; Chromatography; Biology; Botany","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":[0.0001447584,0.0001271535,0.000200788,0.0001978964,0.00015434,0.00004622766,0.00004254674,0.000089645,0.0001337998],"category_scores_gemma":[0.0005948044,0.0001083355,0.00001117347,0.00102508,0.0001693585,0.0001679187,0.00004116709,0.0002525501,0.00003329142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002109168,"about_ca_system_score_gemma":0.0000794456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001891255,"about_ca_topic_score_gemma":0.000004458789,"domain_scores_codex":[0.999052,0.00001875628,0.0002602159,0.0003086792,0.0001769112,0.0001834137],"domain_scores_gemma":[0.9993495,0.0002134293,0.00005716721,0.00009652595,0.0001902897,0.00009309925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001034133,0.003551994,0.2181986,0.01733858,0.0008718852,0.00006111695,0.006887564,0.0006603269,0.004092738,0.008955559,0.1093237,0.6290238],"study_design_scores_gemma":[0.001848387,0.0001648179,0.09633178,0.0001666363,0.0002138952,0.00002781297,0.002356203,0.000534881,0.02367272,0.001152514,0.8732116,0.0003187511],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.893079,0.03669578,0.002122328,0.04294237,0.001014312,0.005894796,0.0002133515,0.0009041732,0.01713386],"genre_scores_gemma":[0.9653548,0.02507222,0.0008140149,0.0007208599,0.004334301,0.000470654,0.0002185607,0.00004552126,0.002969044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7638879,"threshold_uncertainty_score":0.4417794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04005280954070452,"score_gpt":0.347235659923484,"score_spread":0.3071828503827795,"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."}}