{"id":"W4404657156","doi":"10.1186/s13007-024-01304-1","title":"A high-throughput approach for quantifying turgor loss point in grapevine","year":2024,"lang":"en","type":"article","venue":"Plant Methods","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Niagara College; The Scarborough Hospital; University of Toronto","funders":"University of Toronto Scarborough; Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Turgor pressure; Vine; Vitis vinifera; Biology; Drought tolerance; Intraspecific competition; Context (archaeology); Horticulture; Hygrometer; Crop; Viticulture; Agronomy; Botany; Environmental science; Humidity; Ecology; Wine; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00137385,0.0002016362,0.0003161349,0.00002958891,0.0001397113,0.0002016783,0.000247788,0.0001227218,0.0001359882],"category_scores_gemma":[0.0002686188,0.00006010873,0.0001721102,0.0006335231,0.00005363734,0.000216769,0.00008589237,0.0002607127,0.00002036607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004672128,"about_ca_system_score_gemma":0.000009705679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004333988,"about_ca_topic_score_gemma":0.0002396216,"domain_scores_codex":[0.9981237,0.0002701109,0.0003232121,0.000516275,0.0002233315,0.0005433934],"domain_scores_gemma":[0.9984498,0.001287928,0.00003113133,0.00005262235,0.000051355,0.0001271645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001476522,0.0001298776,0.0003667754,0.0002493848,0.00004860587,0.00005828364,0.000337952,0.000024482,0.6607297,0.008763447,0.002136623,0.3270072],"study_design_scores_gemma":[0.002112116,0.002607392,0.09375571,0.001298694,0.0002453867,0.0008457971,0.005291115,0.08570886,0.292617,0.02254057,0.4893094,0.003667969],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984122,0.002238929,0.005678733,0.005153962,0.0004981222,0.001090162,0.0003774138,0.0002720309,0.0005686873],"genre_scores_gemma":[0.8953587,0.000284284,0.1020294,0.0001516995,0.0005409606,0.0002405156,0.0006680929,0.000002731397,0.0007236713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4871728,"threshold_uncertainty_score":0.2451163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1810051011904265,"score_gpt":0.4114661643075053,"score_spread":0.2304610631170788,"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."}}