{"id":"W2602376371","doi":"10.1002/9781118590263.ch7","title":"Sensory Evaluation Techniques for Detecting and Quantifying Bitterness in Food and Beverages","year":2017,"lang":"en","type":"other","venue":"","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Food science; Bitter taste; Taste; Perception; Sensory system; Food products; Caffeine; Masking (illustration); Chemistry; Biochemical engineering; Psychology; Cognitive psychology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00165291,0.001014951,0.0005091368,0.002999545,0.0003672253,0.001288019,0.0009976688,0.0009084425,0.005873399],"category_scores_gemma":[0.002593361,0.0004195841,0.0005882092,0.001966947,0.000474547,0.001433518,0.000753867,0.0009753225,0.002878519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004920674,"about_ca_system_score_gemma":0.0003663712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007141362,"about_ca_topic_score_gemma":0.001864082,"domain_scores_codex":[0.9975956,0.0002355583,0.00008414034,0.0001631823,0.001852838,0.00006864499],"domain_scores_gemma":[0.9983507,0.0004361722,0.0001870334,0.00007423598,0.0009164311,0.00003536354],"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":[0.0002017357,0.0001746643,0.001780099,0.002300007,0.00004495789,0.0002030647,0.0003489921,0.0008718112,0.5363833,0.003191662,0.006682674,0.447817],"study_design_scores_gemma":[0.00002169222,0.001207229,0.01627734,0.0009173928,0.0001397995,0.002724989,0.0009103821,0.01288355,0.8248085,0.003354308,0.1365354,0.0002194019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1461712,0.08360387,0.6626205,0.001168467,0.001182477,0.001798612,0.002792522,0.004176597,0.09648573],"genre_scores_gemma":[0.2509204,0.08570087,0.5923169,0.00113817,0.0002300045,0.00104578,0.001675283,0.0005985103,0.06637413],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005873399,"threshold_uncertainty_score":0.01964849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05661288289173245,"score_gpt":0.3167197846282598,"score_spread":0.2601069017365273,"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."}}