{"id":"W4415721448","doi":"10.5376/tgmb.2025.15.0021","title":"Progress in Breeding of <i>Vitis vinifera</i> for Fruit Quality Improvement","year":2025,"lang":"","type":"article","venue":"Tree Genetics and Molecular Breeding","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quality management; Quality (philosophy); Selection (genetic algorithm); Genomic selection; Plant breeding; Performance improvement","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001090659,0.0005504563,0.0008598617,0.0001197667,0.0004250196,0.0003352303,0.0005998437,0.000392984,0.00005219486],"category_scores_gemma":[0.0002462209,0.0002898591,0.0003873242,0.0009501446,0.000483413,0.0001368671,0.0006436913,0.0002839859,0.000002123882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001193974,"about_ca_system_score_gemma":0.00006916598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001346573,"about_ca_topic_score_gemma":0.001542511,"domain_scores_codex":[0.9955846,0.0001483324,0.001300648,0.001045223,0.0007341742,0.001186997],"domain_scores_gemma":[0.9982597,0.0002995086,0.0003293055,0.0001804576,0.0005850508,0.0003460335],"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":[0.0001018334,0.0001698522,0.004750924,0.000320063,0.00009308799,0.000009211189,0.0001814652,0.000007064314,0.6664382,0.004855589,0.0001398772,0.3229329],"study_design_scores_gemma":[0.00464557,0.008147115,0.4796419,0.002163874,0.0004383555,0.00001620548,0.001931674,0.005078612,0.4684552,0.00376359,0.02364984,0.002068048],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785416,0.01411112,0.0001170492,0.003962538,0.0003281301,0.001667964,0.0001498194,0.00002558868,0.001096256],"genre_scores_gemma":[0.9955245,0.002455099,0.0005544845,0.0001889548,0.000219289,0.0001675402,0.00005923118,0.000007506448,0.0008234199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.474891,"threshold_uncertainty_score":0.9999554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03752837531820155,"score_gpt":0.3162235945953588,"score_spread":0.2786952192771572,"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."}}