{"id":"W4389370978","doi":"10.1007/s44154-023-00127-9","title":"Foliar application of strigolactones improves the desiccation tolerance, grain yield and water use efficiency in dryland wheat through modulation of non-hydraulic root signals and antioxidant defense","year":2023,"lang":"en","type":"article","venue":"Stress Biology","topic":"Plant Parasitism and Resistance","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Key Research and Development Program of China; Agriculture and Agri-Food Canada; National Natural Science Foundation of China","keywords":"Water-use efficiency; Agronomy; Antioxidant; Shoot; Abscisic acid; Yield (engineering); Desiccation; Biomass (ecology); Water content; Biology; Chemistry; Irrigation; Botany; Materials science; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009518336,0.0003279956,0.0003651137,0.0002102568,0.0001190573,0.0002397607,0.0001374643,0.0002245887,0.0006794229],"category_scores_gemma":[0.0000624231,0.000127927,0.0002532003,0.0001362479,0.0001575546,0.0002220578,0.000193605,0.0005722623,0.0001106196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002409439,"about_ca_system_score_gemma":0.0001564304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008741341,"about_ca_topic_score_gemma":0.001650755,"domain_scores_codex":[0.9999466,0.000007211068,0.000007363231,0.00001596212,0.000008746188,0.00001409596],"domain_scores_gemma":[0.9999193,0.000006280503,0.00003056592,0.000007160176,0.000008840852,0.00002789926],"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":[0.000256836,0.00005337657,0.000188292,0.00004425242,0.0000105045,0.00002430866,0.00001013071,0.00002642334,0.9981802,0.00001196207,0.00001543537,0.001178448],"study_design_scores_gemma":[0.0001322051,0.004226741,0.03389383,0.00001667684,0.0001321001,0.0001196731,0.00008865591,0.0008607688,0.957512,0.00008389364,0.002916456,0.00001707994],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979267,0.001127217,0.0004195434,0.00004880129,0.00001521037,0.00000869343,0.0001251508,0.00005436255,0.0002742021],"genre_scores_gemma":[0.9972942,0.0006512462,0.0005911559,0.00007166756,0.000007745228,0.00001083007,0.0002497608,0.00001111509,0.00111229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008741341,"threshold_uncertainty_score":0.002272904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01637775060896744,"score_gpt":0.2407258838582514,"score_spread":0.224348133249284,"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."}}