{"id":"W3036434626","doi":"10.3390/foods9060821","title":"Beer and Consumer Response Using Biometrics: Associations Assessment of Beer Compounds and Elicited Emotions","year":2020,"lang":"en","type":"article","venue":"Foods","topic":"Biochemical Analysis and Sensing Techniques","field":"Nursing","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Alcohol content; Food science; Fermentation; Alcohol; Psychology; Chemistry; Biochemistry","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":[0.0002700792,0.00009049245,0.0002351794,0.0002129182,0.0001150875,0.00004529137,0.00004517067,0.0001001802,0.000007994619],"category_scores_gemma":[0.0003282011,0.00008657649,0.00005299549,0.0008170835,0.0001111781,0.0000485441,0.00005646814,0.000116259,3.391609e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004322987,"about_ca_system_score_gemma":0.00001355191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007528285,"about_ca_topic_score_gemma":0.000002795117,"domain_scores_codex":[0.999162,0.0001328482,0.0002417594,0.0001813676,0.0001647691,0.0001172661],"domain_scores_gemma":[0.9993119,0.0002526898,0.0001166913,0.0001026102,0.0001296513,0.00008645427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008011222,0.00009991298,0.04150747,0.00002902117,0.0001521885,0.000001004281,0.000437015,0.000003912147,0.954105,0.000213809,0.002089662,0.00128089],"study_design_scores_gemma":[0.001765493,0.001176621,0.6887429,0.0001693536,0.001220341,0.00001826672,0.0003926776,0.1541114,0.1419691,0.001891195,0.007733024,0.0008096391],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910143,0.0001885174,0.003719298,0.004697081,0.00003345296,0.00008647455,0.00007049016,0.00006657057,0.0001237861],"genre_scores_gemma":[0.9683787,0.0000120826,0.03107106,0.0004733248,0.00002433266,7.526406e-7,0.00002198881,0.00001063617,0.000007094478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8121359,"threshold_uncertainty_score":0.3530487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06450620523223052,"score_gpt":0.3488524128529241,"score_spread":0.2843462076206936,"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."}}