{"id":"W2758961455","doi":"","title":"Regional-scale digital soil mapping in british columbia using legacy soil survey data and machine-learning techniques","year":2017,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scale (ratio); Digital soil mapping; Soil survey; Remote sensing; Environmental science; Data science; Computer science; Cartography; Forestry; Soil map; Geography; Soil science; Soil water","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0002921055,0.0002567343,0.000190234,0.00186726,0.001119806,0.001202826,0.0008001346,0.0002466302,0.002498273],"category_scores_gemma":[0.001633308,0.0002105377,0.0001675203,0.004716504,0.0004139466,0.0003065726,0.0005802736,0.0003607176,0.000395154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01779893,"about_ca_system_score_gemma":0.01013967,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934931,"about_ca_topic_score_gemma":0.9979108,"domain_scores_codex":[0.9997526,0.00002375005,0.00001108995,0.00005991456,0.00009522987,0.00005740865],"domain_scores_gemma":[0.9986975,0.0001807369,0.00006412568,0.00007445124,0.0008731249,0.0001099357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003610839,0.0002373309,0.6812485,0.0003898351,0.0002088108,0.001521806,0.002891567,0.02810491,0.005087772,0.001862193,0.02064054,0.2574456],"study_design_scores_gemma":[0.00002604223,0.00002636879,0.9483561,0.0001109525,0.00005981525,0.0001125993,0.006133996,0.02730033,0.001236877,0.000293408,0.01628958,0.00005394075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747916,0.0003388549,0.0009800286,0.0002913911,0.000007381421,0.00009980801,0.01018186,0.0001829457,0.0131261],"genre_scores_gemma":[0.982726,0.0003802321,0.00313408,0.00006094387,0.000002337407,0.00005387759,0.005854429,0.00003348617,0.007754649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01779893,"threshold_uncertainty_score":0.1291409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02813760729104563,"score_gpt":0.2307214545110876,"score_spread":0.2025838472200419,"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."}}