{"id":"W4413260195","doi":"10.1270/jsbbs.25011","title":"Inheritance characteristics and potential of genomic prediction for pungency levels in F<sub>1</sub> progeny of chili pepper (<i>Capsicum annuum</i>)","year":2025,"lang":"en","type":"article","venue":"Breeding Science","topic":"Agricultural Practices and Plant Genetics","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Institute of Genetics; University of Tokyo","keywords":"Pungency; Capsicum annuum; Biology; Pepper; Chili pepper; Horticulture; Inheritance (genetic algorithm); Genetics; Botany; Biotechnology; Gene","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":[0.0009974299,0.0002696021,0.0003985116,0.00008191554,0.0004350383,0.0001405461,0.0006371209,0.0001795447,0.00002186485],"category_scores_gemma":[0.0002853915,0.0001352498,0.0001072114,0.001018749,0.0004870173,0.0005824654,0.0002419921,0.0001542787,0.000002869761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006562681,"about_ca_system_score_gemma":0.00008466015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001863374,"about_ca_topic_score_gemma":0.0002199351,"domain_scores_codex":[0.9975246,0.00005458348,0.000686946,0.0006704879,0.0005050911,0.0005583099],"domain_scores_gemma":[0.9986833,0.0001925667,0.0004707922,0.0001186011,0.0003992025,0.0001354814],"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":[0.00005754468,0.00009652538,0.00655572,0.00006630422,0.00001275742,0.000001574098,0.0001752919,0.00003179357,0.9727814,0.0007371753,0.0002753027,0.01920861],"study_design_scores_gemma":[0.0002943626,0.00046505,0.9437354,0.0001691488,0.00005752789,0.00002268824,0.000112719,0.002207213,0.04818517,0.0002717281,0.004191259,0.0002877181],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958552,0.001042709,0.00006945144,0.000586308,0.0006161348,0.0007376479,0.0006186891,0.00003658789,0.0004373174],"genre_scores_gemma":[0.998107,0.0007335513,0.0005750773,0.00005438569,0.0002682787,0.00003068968,0.00004791002,0.00000249305,0.0001806656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9371797,"threshold_uncertainty_score":0.5515326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861256160489498,"score_gpt":0.2235979794152061,"score_spread":0.2049854178103111,"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."}}