{"id":"W2591201481","doi":"","title":"An analytical approach from natural sources ob bioactive compounds to nutraceuticals and functional foods: Development of extraction, characterization and bioactivity evaluation strategies","year":2016,"lang":"en","type":"dissertation","venue":"Dialnet (Universidad de la Rioja)","topic":"Natural Products and Biological Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nutraceutical; Characterization (materials science); Extraction (chemistry); Biochemical engineering; Chemistry; Traditional medicine; Computational biology; Biotechnology; Nanotechnology; Biology; Food science; Engineering; Medicine; Materials science; Chromatography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002326382,0.0012258,0.0006284715,0.001724577,0.0004922387,0.001340024,0.0007887952,0.001133988,0.001255159],"category_scores_gemma":[0.001243943,0.0005209704,0.0009133531,0.0009119352,0.0007878551,0.00175483,0.001218581,0.002114693,0.001823489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006467304,"about_ca_system_score_gemma":0.001524691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004261746,"about_ca_topic_score_gemma":0.0008545947,"domain_scores_codex":[0.9982989,0.0003383677,0.0001156536,0.0003678325,0.0007761628,0.0001030511],"domain_scores_gemma":[0.9993579,0.0001927516,0.00008984905,0.00005499422,0.000274406,0.00003017291],"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":[0.00007260616,0.0001506716,0.0004322241,0.001256318,0.0000804301,0.0001555758,0.0001601363,0.0004411483,0.9293311,0.001852479,0.000851386,0.065216],"study_design_scores_gemma":[0.00001493202,0.000405802,0.001678114,0.0002526277,0.0000922586,0.0007885552,0.0001625359,0.001884634,0.9497658,0.001257587,0.04363977,0.00005740646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1408095,0.0816367,0.75213,0.002892506,0.0008339937,0.001878676,0.001734198,0.000821401,0.017263],"genre_scores_gemma":[0.2245084,0.07934742,0.6708242,0.003002773,0.0004575485,0.001761926,0.001710765,0.0002283072,0.01815872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002326382,"threshold_uncertainty_score":0.01230323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04499370959684323,"score_gpt":0.3594153034917922,"score_spread":0.3144215938949489,"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."}}