{"id":"W6997118517","doi":"","title":"Using hyperspectral remote sensing to map grape quality in 'Tempranillo' vineyards affected by iron deficiency chlorosis","year":2015,"lang":"en","type":"article","venue":"Federal Research Centre for Cultivated Plants (Julius Kühn-Institut)","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"York University","keywords":"Hyperspectral imaging; Chlorosis; Iron deficiency; Reflectivity; Quality (philosophy)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001799902,0.000218876,0.0002027744,0.0004238476,0.0002719359,0.0005828108,0.0001988315,0.0002675234,0.0002717708],"category_scores_gemma":[0.0002438631,0.0001111396,0.000170302,0.0002328873,0.0001694041,0.0001224879,0.0001680019,0.0001739444,0.0000535537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004726372,"about_ca_system_score_gemma":0.0001343953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05657582,"about_ca_topic_score_gemma":0.09222214,"domain_scores_codex":[0.9999009,0.00001771635,0.000005415396,0.00003700469,0.00001955989,0.00001946291],"domain_scores_gemma":[0.999889,0.00002403624,0.00002083515,0.000007372096,0.00003115993,0.00002754994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001741868,0.0002939572,0.8005176,0.00005060601,0.000198438,0.0006390623,0.0008738458,0.001077379,0.1820861,0.00005641978,0.0002266356,0.01223807],"study_design_scores_gemma":[0.000005342234,0.00004594658,0.9967469,0.000002095465,0.00002015338,0.0001045912,0.0003476225,0.001273517,0.001362584,0.000008294084,0.00007925158,0.000003636929],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999797,0.00001557569,0.00005308488,0.000003664845,0.000001098168,0.000001702213,0.00003448348,0.000002406712,0.00009096268],"genre_scores_gemma":[0.9995928,0.00001298339,0.0001378006,0.000004585186,6.030203e-7,0.000001204568,0.00009954382,0.000001422612,0.0001490237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05657582,"threshold_uncertainty_score":0.112493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1509192388625369,"score_gpt":0.3771197063213218,"score_spread":0.2262004674587849,"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."}}