{"id":"W2150993898","doi":"","title":"MAPPING OF SOIL CONDITIONS IN PRECISION AGRICULTURE","year":2009,"lang":"en","type":"article","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humus; Topsoil; Soil science; Soil texture; Precision agriculture; Soil map; Sampling (signal processing); Texture (cosmology); Environmental science; Mathematics; Soil water; Geography; Agriculture","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004799922,0.0002301957,0.0002394525,0.001540038,0.0002483054,0.0008312925,0.0003090903,0.0003576615,0.0005722203],"category_scores_gemma":[0.001299763,0.0001264643,0.0001514979,0.002780481,0.0003576783,0.000465532,0.0005130693,0.0001459735,0.0001931879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006857213,"about_ca_system_score_gemma":0.0004226245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01610571,"about_ca_topic_score_gemma":0.02344327,"domain_scores_codex":[0.9993541,0.0001241765,0.00002680457,0.0002282127,0.0002065323,0.00006015703],"domain_scores_gemma":[0.9992884,0.000177277,0.0002249619,0.0001020783,0.0001813191,0.00002606734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003188325,0.00008499273,0.6632158,0.0003004039,0.0001524312,0.0004136375,0.000616167,0.02295257,0.03311192,0.0006066523,0.0006993562,0.2775272],"study_design_scores_gemma":[0.0000117474,0.00009598128,0.9845761,0.00002263234,0.00002533723,0.0001671514,0.0003015938,0.009235137,0.003176068,0.0005541177,0.001820499,0.00001352687],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982812,0.0007081723,0.0106394,0.00004652549,0.000006945687,0.00004003388,0.0008278936,0.0001733496,0.004745753],"genre_scores_gemma":[0.9960998,0.0001299853,0.003318591,0.000007341259,0.000003222346,0.00000989632,0.0002428612,0.000005606174,0.0001826636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01610571,"threshold_uncertainty_score":0.03202391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008901406873677247,"score_gpt":0.2262693279358546,"score_spread":0.2173679210621774,"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."}}