{"id":"W7162071187","doi":"10.82308/29566","title":"Optimization of sampling designs for validating digital soil maps","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital soil mapping; Sampling (signal processing); Latin hypercube sampling; Kriging; Sampling design; Soil map; Stratified sampling; Simple random sample; Precision agriculture; Sample (material)","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":[0.0179766,0.0009185511,0.0005994947,0.001420533,0.0004557217,0.000811577,0.001266395,0.0005726386,0.002756998],"category_scores_gemma":[0.04541557,0.000618398,0.0006517174,0.001315304,0.0005157356,0.0006335027,0.00121179,0.0004574592,0.0007047481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007858778,"about_ca_system_score_gemma":0.00133799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003440379,"about_ca_topic_score_gemma":0.003616792,"domain_scores_codex":[0.9914448,0.005517555,0.0006824168,0.0008344975,0.001276957,0.0002438682],"domain_scores_gemma":[0.9671359,0.01871249,0.002251171,0.00438,0.007191908,0.0003285097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001440313,0.0005688566,0.04003167,0.0009573606,0.0001879266,0.0001966178,0.0003661237,0.5377213,0.05296307,0.008462205,0.001512732,0.3555918],"study_design_scores_gemma":[0.0003658267,0.001529048,0.01970899,0.0001101051,0.0001237484,0.0001157542,0.0002219734,0.9153383,0.04954927,0.006894082,0.005979754,0.00006308685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06828228,0.0000728554,0.9277048,0.00004240279,0.00002895882,0.001411546,0.0005263981,0.0007133402,0.001217501],"genre_scores_gemma":[0.200065,0.00007443978,0.7967312,0.00002996204,0.000009517012,0.002052649,0.0007023477,0.00007281885,0.0002619571],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0179766,"threshold_uncertainty_score":0.09507048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0352987103239939,"score_gpt":0.2775347353033806,"score_spread":0.2422360249793867,"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."}}