{"id":"W4392901834","doi":"10.1109/tafe.2024.3369995","title":"Mapping Soil Organic Matter Under Field Conditions","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on AgriFood Electronics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Field (mathematics); Environmental science; Soil science; Soil organic matter; Organic matter; Soil water; Mathematics; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00008636812,0.0001685046,0.0001119112,0.0000844139,0.0002507842,0.00009863996,0.0001393158,0.00009859653,0.009711235],"category_scores_gemma":[0.000001999646,0.0001638426,0.00009104677,0.0004546385,0.00004777675,0.0001376244,0.000002778693,0.0004551061,0.0045976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002641017,"about_ca_system_score_gemma":0.00004758709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007738791,"about_ca_topic_score_gemma":0.0005438912,"domain_scores_codex":[0.9988157,0.00002497269,0.0001863251,0.0003439004,0.0002071707,0.0004219988],"domain_scores_gemma":[0.99953,0.0001438325,0.00002193776,0.0002106108,0.000006904864,0.00008672648],"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":[0.0000825668,0.001138441,0.0002623502,0.0002798299,0.001103056,0.0001219143,0.003190679,0.2113953,0.4611512,0.01028364,0.1976219,0.113369],"study_design_scores_gemma":[0.002428633,0.002535163,0.007943118,0.000668154,0.0007119385,0.0007161672,0.001838067,0.1227187,0.4636982,0.0810907,0.31118,0.004471213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09871057,0.0001637906,0.8869708,0.002902255,0.000793217,0.0001973131,0.00004244258,0.0002492893,0.00997034],"genre_scores_gemma":[0.9941155,0.0001342354,0.0002282913,0.001705783,0.00003923369,0.00003740955,0.000008247933,0.000031644,0.003699664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8954049,"threshold_uncertainty_score":0.9961774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007971177000952897,"score_gpt":0.2208235667936455,"score_spread":0.2128523897926926,"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."}}