{"id":"W3211595198","doi":"10.1002/jsfa.11635","title":"Applied <scp>GA<sub>5</sub></scp>, <scp>GA<sub>4</sub>,</scp> and <scp>GA<sub>4/7</sub></scp> increase berry number per bunch, yield, and grape quality for winemaking in <scp><i>Vitis vinifera</i> L. cv. Malbec</scp>","year":2021,"lang":"en","type":"article","venue":"Journal of the Science of Food and Agriculture","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fondo para la Investigación Científica y Tecnológica; Universidad Nacional de Cuyo","keywords":"Berry; Gibberellin; Horticulture; Veraison; Chemistry; Yield (engineering); Winemaking; Powdery mildew; Sugar; Wine; Biology; Food science; Physics","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":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002960636,0.001093616,0.001603976,0.0001608301,0.001892687,0.001214457,0.001451257,0.0007512107,0.000008561204],"category_scores_gemma":[0.006469047,0.0004477348,0.0007820931,0.002791969,0.001487674,0.001689268,0.001067096,0.001727153,0.00001461252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175525,"about_ca_system_score_gemma":0.0002531765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001068253,"about_ca_topic_score_gemma":0.001215392,"domain_scores_codex":[0.99153,0.0005098108,0.001829545,0.001587833,0.002474533,0.002068256],"domain_scores_gemma":[0.991245,0.003907306,0.001473961,0.0003541266,0.001630485,0.001389099],"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":[0.00002242283,0.000437466,0.003337411,0.0002113489,0.0001379021,0.00005138959,0.001741265,0.00002984343,0.9760178,0.0003434459,0.009271744,0.008397982],"study_design_scores_gemma":[0.001161568,0.0007596025,0.2403685,0.0005744235,0.0001826167,0.0009415486,0.01559947,0.00002369277,0.7359465,0.001277663,0.002954554,0.0002098295],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926528,0.002336731,0.000004211927,0.001735282,0.000470821,0.001101767,0.0002655037,0.00006240515,0.001370508],"genre_scores_gemma":[0.9946664,0.002785824,0.0001630923,0.0006770052,0.001160607,0.00007275719,0.00005176635,0.0000171265,0.0004054444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2400713,"threshold_uncertainty_score":0.9998224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02074263639621676,"score_gpt":0.2485724950235257,"score_spread":0.2278298586273089,"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."}}