{"id":"W2983878793","doi":"10.32352/0367-3057.5.19.01","title":"Research of the current state of the vitaminary preparations market in Ukraine","year":2019,"lang":"en","type":"article","venue":"Farmatsevtychnyi zhurnal","topic":"Agriculture and Biological Studies","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Current (fluid); State (computer science); Business; Political science; Computer science; Engineering; Electrical engineering","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":[0.0008585632,0.0001229691,0.0002149662,0.003340633,0.0005455376,0.002065545,0.000360827,0.0002997375,0.004182367],"category_scores_gemma":[0.001633638,0.0001464406,0.0003255476,0.003351825,0.0004923489,0.001687094,0.0007222776,0.0003572866,0.0007012235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002054494,"about_ca_system_score_gemma":0.002391404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01031866,"about_ca_topic_score_gemma":0.007454484,"domain_scores_codex":[0.9989568,0.0001229878,0.0001334001,0.0002331401,0.0004228253,0.000130838],"domain_scores_gemma":[0.9983245,0.0002934985,0.0007417469,0.00006256255,0.0004688975,0.0001087873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007301538,0.0003260807,0.4416413,0.003035112,0.000175639,0.003746441,0.01713208,0.001815339,0.0224798,0.0398667,0.01169117,0.4573601],"study_design_scores_gemma":[0.000008423604,0.0002984552,0.8025479,0.0005452648,0.00006943697,0.001860778,0.01081774,0.001402622,0.005644233,0.001795561,0.174956,0.00005349594],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9361338,0.0171295,0.0008296267,0.001911687,0.0000563817,0.00004971527,0.003404916,0.00006197316,0.04042243],"genre_scores_gemma":[0.9808006,0.00989662,0.00119767,0.0002635516,0.00005005971,0.00002207941,0.001608039,0.00002168827,0.006139694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01031866,"threshold_uncertainty_score":0.02051723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04034635553010157,"score_gpt":0.3035336463031353,"score_spread":0.2631872907730338,"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."}}