{"id":"W4409359989","doi":"10.1016/j.sajb.2025.03.065","title":"Genetic control of fruit quality characters in the segregating generations of interspecific crosses and metabolic profiling of the fruits of promising segregants of tomato","year":2025,"lang":"en","type":"article","venue":"South African Journal of Botany","topic":"Agricultural Practices and Plant Genetics","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Institute of Genetics; Bulgarian Academy of Sciences","keywords":"Interspecific competition; Biology; Profiling (computer programming); Horticulture; Biotechnology; Botany; Computer science","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":[0.0008870233,0.0001033157,0.0004520409,0.00002816644,0.00006614425,0.00001878513,0.0003228867,0.00004979508,0.000006842763],"category_scores_gemma":[0.0003590538,0.00003290375,0.0001439316,0.0004785272,0.0001813871,0.00008173176,0.00004426542,0.0001527186,3.301823e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006472607,"about_ca_system_score_gemma":0.00004192566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008156811,"about_ca_topic_score_gemma":0.00009678765,"domain_scores_codex":[0.9981353,0.0003742253,0.0009825557,0.00009867175,0.0002881361,0.0001211306],"domain_scores_gemma":[0.9970136,0.0005957651,0.00194619,0.00007356388,0.0003430781,0.00002779259],"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":[0.00008835347,0.00006564317,0.1582147,0.00005614589,0.00006387647,5.601827e-7,0.003765875,0.00008160624,0.8353021,0.0001702752,0.000002869097,0.002188004],"study_design_scores_gemma":[0.0003217222,0.0001620565,0.8488499,0.0002787635,0.0001100453,0.00001180471,0.02272731,0.00009745119,0.127239,0.0001206011,0.00001658441,0.00006469517],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972876,0.001811841,0.00002525624,0.0003945646,0.00006011404,0.0002357672,0.0001364154,9.942439e-7,0.00004739498],"genre_scores_gemma":[0.9994721,0.00007877918,0.0003775348,0.00001921313,0.00004127585,0.000001197544,6.850818e-7,7.153076e-7,0.000008460006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7080631,"threshold_uncertainty_score":0.1341776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02474861141416258,"score_gpt":0.2536640054783459,"score_spread":0.2289153940641833,"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."}}