{"id":"W2015133526","doi":"10.1111/j.1439-0396.2007.00778.x","title":"Optimizing the sensory characteristics and acceptance of canned cat food: use of a human taste panel","year":2008,"lang":"en","type":"article","venue":"Journal of Animal Physiology and Animal Nutrition","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Charles Sturt University; Univerzita Karlova v Praze","keywords":"Flavour; Food science; Chewiness; Flavor; Taste; Organoleptic; Aroma; Chemistry; Quantitative Descriptive Analysis; Texture (cosmology); Sensory analysis; Mathematics; Artificial intelligence; Computer science","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":[0.0002107897,0.0001159504,0.0003670263,0.00001753269,0.0002205393,0.00001134438,0.0001009048,0.00008372039,0.00001971503],"category_scores_gemma":[0.0000633753,0.00004719697,0.00009079838,0.00009348824,0.0003664145,0.0002219896,0.00004641227,0.0001547242,2.018701e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005910814,"about_ca_system_score_gemma":0.000007557561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003453105,"about_ca_topic_score_gemma":0.00001167587,"domain_scores_codex":[0.9989997,0.0001485197,0.0004462625,0.0001444361,0.0001170473,0.0001440856],"domain_scores_gemma":[0.9990143,0.0001655347,0.000531508,0.00003538467,0.000197249,0.00005602567],"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":[0.00111157,0.0001654295,0.003230479,0.00007265621,0.00002278318,0.000006070871,0.0002108244,1.940573e-7,0.9944921,0.0002525375,0.00005666792,0.0003786883],"study_design_scores_gemma":[0.0003247576,0.006283056,0.9301707,0.00007814914,0.00003252018,0.0001901997,0.0004571743,0.00002077512,0.06189804,0.0003107819,0.000128774,0.0001051334],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989315,0.0004400068,5.025879e-7,0.0004401111,0.00002655242,0.00009147539,0.00005892137,0.000004132589,0.000006853117],"genre_scores_gemma":[0.9987288,0.0006822806,0.0001608351,0.00007848774,0.0003337115,0.000001026144,0.000007210564,0.000001176708,0.000006470702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9325941,"threshold_uncertainty_score":0.1924636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1112264478974836,"score_gpt":0.2640391171513009,"score_spread":0.1528126692538173,"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."}}