{"id":"W2792036082","doi":"10.5539/jas.v10n4p351","title":"Separation of Cultivars of Soybeans by Chemometric Methods Using Near Infrared Spectroscopy","year":2018,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chemometrics; Principal component analysis; Cultivar; Spectroscopy; Near-infrared spectroscopy; Mathematics; Analytical Chemistry (journal); Chemistry; Biological system; Chromatography; Statistics; Botany; Optics; Biology; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0007064535,0.0001477289,0.0004256883,0.0002906132,0.0001755037,0.00006259031,0.0005993496,0.00008130597,0.0003455919],"category_scores_gemma":[0.0006925783,0.00009038945,0.000173869,0.00512173,0.0007612105,0.0006491378,0.0000681059,0.0001921052,0.00000164106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002270848,"about_ca_system_score_gemma":0.0001915066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004213676,"about_ca_topic_score_gemma":6.857063e-7,"domain_scores_codex":[0.9980779,0.00002660709,0.0006815093,0.0001864,0.0007487201,0.0002788565],"domain_scores_gemma":[0.9972878,0.0001111473,0.001251848,0.0001541886,0.001054815,0.0001402184],"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":[0.00002057009,0.00008212298,0.002168426,0.00002050313,0.00004156971,4.277803e-7,0.0002833056,0.00003517935,0.9962407,0.00001467026,0.0009051643,0.0001873522],"study_design_scores_gemma":[0.0002519838,0.0001873178,0.01073129,0.00003680516,0.0001210376,0.00005594327,0.0007733828,0.000286736,0.9872268,0.00006391629,0.0001474049,0.0001173504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911388,0.0004289381,0.003926557,0.00004746351,0.000102913,0.00002890797,0.000006642415,0.000007001874,0.004312835],"genre_scores_gemma":[0.9127426,0.00004155705,0.086755,0.00001152446,0.0001508302,2.533054e-7,0.000001243011,0.000004249489,0.0002928028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08282844,"threshold_uncertainty_score":0.3783989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02329376918490428,"score_gpt":0.3728390389686572,"score_spread":0.3495452697837529,"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."}}