{"id":"W4408072020","doi":"10.1016/j.foodchem.2025.143658","title":"Ripening-stage variations in small metabolites across six banana cultivars: A metabolomic perspective","year":2025,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Banana Cultivation and Research","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"South China Botanical Garden, Chinese Academy of Sciences; National Key Research and Development Program of China Stem Cell and Translational Research; Guangzhou Municipal Science and Technology Bureau; National Key Research and Development Program of China; Government of Guangdong Province; Chinese Academy of Sciences","keywords":"Ripening; Metabolomics; Cultivar; Stage (stratigraphy); Biology; Horticulture; Botany; Bioinformatics","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":[0.0002479482,0.0001527835,0.0002168055,0.00001470571,0.0002158407,0.00009662024,0.0003427574,0.0001556088,0.0003961491],"category_scores_gemma":[0.0003372442,0.00006797115,0.0001144056,0.0009111828,0.00008300228,0.00008022945,0.0001324934,0.0002791541,0.0000182621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009405819,"about_ca_system_score_gemma":0.00004011344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008813167,"about_ca_topic_score_gemma":0.001520546,"domain_scores_codex":[0.9988133,0.00005653128,0.0002273644,0.0003902175,0.0001332559,0.0003792742],"domain_scores_gemma":[0.99946,0.0001651433,0.00006401246,0.00009169764,0.0001411816,0.0000779303],"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":[0.00003247344,0.0001878932,0.003607362,0.00002308747,0.0000778664,0.000003010166,0.0004864422,0.000008333339,0.9861968,0.004346407,0.0003342749,0.004696071],"study_design_scores_gemma":[0.00074976,0.00004228592,0.1518792,0.00005902462,0.00002413229,0.000001778025,0.01015437,0.0002239544,0.7960648,0.001148723,0.03928987,0.0003621566],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802149,0.0008843241,0.00001296811,0.00239921,0.00005183749,0.0001769124,0.0001809942,0.00006463769,0.01601425],"genre_scores_gemma":[0.9904363,0.00004019007,0.0001427135,0.0001103245,0.00008572517,0.00005114796,0.00006969368,0.000001135508,0.009062763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.190132,"threshold_uncertainty_score":0.4337555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02922346039159015,"score_gpt":0.2929479982145389,"score_spread":0.2637245378229487,"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."}}