{"id":"W2096615175","doi":"10.1016/j.lwt.2010.06.016","title":"Microstructure and physico-chemical bases of textural quality of yam products","year":2010,"lang":"en","type":"article","venue":"LWT","topic":"Food composition and properties","field":"Nursing","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Universitaire de la Francophonie","keywords":"Microstructure; Quality (philosophy); Texture (cosmology); Materials science; Business; Chemistry; Metallurgy; Computer science; Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002737967,0.00005652277,0.0001257277,0.00001377248,0.0000198648,0.00000760753,0.00005425037,0.00003905596,0.00002185985],"category_scores_gemma":[0.0000527233,0.00004336682,0.00002415343,0.00004603266,0.0001454682,0.00004595871,0.00002122122,0.0001028705,0.000001278692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002164786,"about_ca_system_score_gemma":0.00000226444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007027639,"about_ca_topic_score_gemma":0.000005723882,"domain_scores_codex":[0.9996088,0.00002600901,0.0001254574,0.0001003065,0.00007322925,0.00006623751],"domain_scores_gemma":[0.9996843,0.00002740842,0.00006068209,0.0001434585,0.00006444698,0.00001965018],"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":[0.0003195275,0.00002213949,0.0006827299,0.0001242108,0.000005080441,5.798013e-8,0.0005004319,1.89861e-7,0.9906491,0.0001539824,0.0005135271,0.007029017],"study_design_scores_gemma":[0.0001940643,0.0000919419,0.01038475,0.00001706979,0.000006635732,0.000004090381,0.00004233464,0.000007753458,0.9868788,0.0003589613,0.001957402,0.00005618666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980683,0.0001051965,4.561095e-7,0.001058608,0.0002455191,0.00005936159,0.00001795339,0.00001487432,0.000429766],"genre_scores_gemma":[0.9989292,5.404234e-7,0.0008067452,0.000118548,0.0001016125,8.222582e-7,0.000007197179,0.000004889201,0.00003045713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009702023,"threshold_uncertainty_score":0.1768448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940645475061459,"score_gpt":0.2778549346467395,"score_spread":0.258448479896125,"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."}}