{"id":"W3188910273","doi":"10.1002/cjce.24283","title":"<scp>ANN</scp> ‐based modelling of peppermint flavour encapsulation process with ultrasound approach","year":2021,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Microencapsulation and Drying Processes","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Encapsulation (networking); Flavour; Artificial neural network; Particle size; Biological system; Process engineering; Computer science; Spray drying; Materials science; Chemistry; Artificial intelligence; Chromatography; Chemical engineering; Engineering; Food science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001704737,0.00009859034,0.0001569298,0.00002289068,0.00006905408,0.00005668524,0.0001857088,0.00005967532,0.00002311097],"category_scores_gemma":[0.0002327723,0.00003941898,0.00006135597,0.0003412199,0.00004008745,0.0000866699,0.000004297476,0.0001917366,5.806184e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003631314,"about_ca_system_score_gemma":0.0002113549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001885644,"about_ca_topic_score_gemma":0.0001108875,"domain_scores_codex":[0.999272,0.00001320782,0.0002386007,0.00009551614,0.0001902068,0.0001904365],"domain_scores_gemma":[0.9991198,0.000183162,0.0001347283,0.00004053246,0.0003230382,0.0001986936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000394261,0.00001757556,0.0005093666,0.00006157989,0.00001968924,0.000008566387,0.0004478481,0.5527881,0.4457609,0.0001082919,0.00003175312,0.0002423493],"study_design_scores_gemma":[0.0002648879,0.0000549773,0.0009600302,0.0002056727,0.0000448216,0.0002963187,0.0003905776,0.1182892,0.8784539,0.0002244008,0.000695841,0.0001194018],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966084,0.0003007684,0.00259479,0.0001897583,0.00002928698,0.00004228058,0.00000583223,0.000007942442,0.0002209619],"genre_scores_gemma":[0.9986176,0.000001880943,0.001174558,0.00005093241,0.0001110572,0.000001322909,0.00001318477,0.000002089707,0.00002732331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.434499,"threshold_uncertainty_score":0.1607459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951126176687869,"score_gpt":0.1799462213563661,"score_spread":0.1604349595894874,"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."}}