{"id":"W4388084103","doi":"10.1002/saj2.20607","title":"Evaluation of two miniaturized FT‐NIR spectrometers for rapid soil property analysis","year":2023,"lang":"en","type":"article","venue":"Soil Science Society of America Journal","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canada First Research Excellence Fund","keywords":"Spectrum analyzer; Spectrometer; Partial least squares regression; Computer science; Soil test; Diffuse reflectance infrared fourier transform; Environmental science; Wavelet; Remote sensing; Precision agriculture; Soil science; Artificial intelligence; Optics; Soil water; Machine learning; Chemistry; Telecommunications; Geology; Physics","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":[0.002160229,0.0007185473,0.0004750956,0.0006761579,0.0003073235,0.0006651462,0.001220339,0.0008855581,0.0009208473],"category_scores_gemma":[0.002497369,0.0004004417,0.000356118,0.0006131466,0.0002943733,0.0009172632,0.0004075887,0.0004179293,0.0003149066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000787607,"about_ca_system_score_gemma":0.0006263055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002835784,"about_ca_topic_score_gemma":0.005710392,"domain_scores_codex":[0.9992349,0.0001433804,0.00003288945,0.0002053377,0.0003506338,0.00003285775],"domain_scores_gemma":[0.9987938,0.0004894591,0.0001107406,0.00008673168,0.0004348014,0.00008436522],"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":[0.002003751,0.001472971,0.0245894,0.0003177057,0.000187539,0.0001251837,0.0001111328,0.01881037,0.8287441,0.0004762755,0.001458364,0.1217033],"study_design_scores_gemma":[0.0003701606,0.004810552,0.04832894,0.00002644994,0.0002009603,0.0004697054,0.0001844111,0.4550489,0.4857621,0.0003285582,0.004356328,0.000112906],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9142169,0.0004373338,0.08206964,0.000222711,0.000140086,0.0002670331,0.0005880083,0.001065915,0.0009924524],"genre_scores_gemma":[0.8724095,0.0003224955,0.1252833,0.0001559598,0.0000321629,0.0001718417,0.0005461879,0.0000658003,0.001012794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002835784,"threshold_uncertainty_score":0.01142454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03298394884141755,"score_gpt":0.3080672722883637,"score_spread":0.2750833234469461,"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."}}