{"id":"W4281398725","doi":"10.1111/joss.12751","title":"Temporal ranking for characterization and improved discrimination of protein beverages","year":2022,"lang":"en","type":"article","venue":"Journal of Sensory Studies","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Ranking (information retrieval); Sucralose; Rank (graph theory); Computer science; Sensory system; Food science; Paired comparison; Mathematics; Artificial intelligence; Statistics; Psychology; Chemistry; Cognitive psychology","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":[0.002680741,0.0005990284,0.000452409,0.001075705,0.000236148,0.0006231085,0.0005955217,0.0005162861,0.003553963],"category_scores_gemma":[0.004693395,0.0002581674,0.0005699024,0.0006271139,0.0002836388,0.0009004724,0.0006903994,0.0006095826,0.000623083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002222207,"about_ca_system_score_gemma":0.0004113957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001097919,"about_ca_topic_score_gemma":0.002690258,"domain_scores_codex":[0.9983985,0.0005727802,0.00009055874,0.000236129,0.000620548,0.00008147322],"domain_scores_gemma":[0.9971323,0.0007527175,0.0006496613,0.000279643,0.001024681,0.0001611101],"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":[0.002538945,0.0006331307,0.0199715,0.0008375103,0.0001461411,0.00007839583,0.000363858,0.003048633,0.6102808,0.0008344385,0.001650141,0.3596165],"study_design_scores_gemma":[0.000314428,0.01297092,0.3255109,0.0001997699,0.0005812394,0.001374537,0.001275805,0.1721504,0.4671597,0.002852249,0.01504439,0.0005656212],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6246451,0.001323585,0.3634148,0.0002664261,0.0002700668,0.000759235,0.0007021552,0.001133235,0.007485431],"genre_scores_gemma":[0.7329434,0.0008041153,0.2608772,0.0002565832,0.0001171965,0.000443602,0.0004184591,0.0001559242,0.003983526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003553963,"threshold_uncertainty_score":0.01417726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08184492740902317,"score_gpt":0.318233171556971,"score_spread":0.2363882441479478,"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."}}