{"id":"W1615052087","doi":"10.1002/jsfa.7334","title":"Use of descriptive analysis and preference mapping for early‐stage assessment of new and established apples","year":2015,"lang":"en","type":"article","venue":"Journal of the Science of Food and Agriculture","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wind Energy Institute of Canada; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Preference; Descriptive statistics; Stage (stratigraphy); Biology; Food science; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008134499,0.00008249805,0.0003647204,0.00004249468,0.00009462379,0.00007256711,0.0001977802,0.00004038441,0.000003258218],"category_scores_gemma":[0.0004854389,0.00002298679,0.0001078151,0.0009267061,0.0003135766,0.0002958442,0.00007522583,0.00008043292,3.802222e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008306405,"about_ca_system_score_gemma":0.00003043459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001390486,"about_ca_topic_score_gemma":0.00008567166,"domain_scores_codex":[0.9989889,0.00008093555,0.0003374614,0.0001392192,0.0003432189,0.0001103159],"domain_scores_gemma":[0.998495,0.0002818176,0.0005638305,0.00004026415,0.0004697947,0.0001492487],"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":[0.00003216865,0.00005549931,0.02288708,0.0000214867,0.0001556601,2.567925e-7,0.0007142731,0.0001043277,0.9657887,0.001453212,0.00009247843,0.008694857],"study_design_scores_gemma":[0.0001905667,0.0008547961,0.9380307,0.00007191474,0.0003443562,0.000006725461,0.003778031,0.0004264395,0.05413984,0.001965001,0.0001042708,0.0000873203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984139,0.0001868402,0.000928487,0.0002699975,0.00003017084,0.00009104369,0.00005592949,9.496747e-7,0.00002264944],"genre_scores_gemma":[0.9803512,0.00006316871,0.01947849,0.00000766326,0.00002788928,4.579513e-7,6.294916e-7,2.460752e-7,0.00007025091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9151437,"threshold_uncertainty_score":0.1155386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1750031233594401,"score_gpt":0.3056640508617367,"score_spread":0.1306609275022966,"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."}}