{"id":"W3016978600","doi":"10.14288/1.0389816","title":"Digital soil mapping to enhance climate change mitigation and adaptation in the Lower Fraser Valley using remote sensing","year":2020,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remote sensing; Climate change; Digital elevation model; Environmental science; Adaptation (eye); Climate change adaptation; Environmental resource management; Geography; Hydrology (agriculture); Geology; Oceanography; Geotechnical engineering","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":[0.000224911,0.0003377776,0.0001568501,0.001421362,0.000326725,0.0008220612,0.0004295191,0.000213909,0.000784497],"category_scores_gemma":[0.0005763681,0.0001386804,0.0001790947,0.001977717,0.0001813073,0.0003632869,0.0003056282,0.0002083113,0.0001178963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001854418,"about_ca_system_score_gemma":0.001517915,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5140251,"about_ca_topic_score_gemma":0.7068797,"domain_scores_codex":[0.999896,0.00001010235,0.000004083668,0.00002889896,0.00003469836,0.00002621717],"domain_scores_gemma":[0.9998228,0.00003260587,0.00002429817,0.00001528702,0.00008010887,0.00002492755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002546477,0.0003301416,0.3681384,0.0003217351,0.0001341342,0.0004521986,0.001181656,0.11997,0.04068543,0.001563454,0.0049753,0.4619928],"study_design_scores_gemma":[0.00006321572,0.00008617489,0.6397651,0.00009705568,0.00007704127,0.0001143723,0.001898819,0.3364595,0.00937843,0.0008254624,0.01117507,0.00005975345],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810988,0.0004399768,0.008404216,0.0003026972,0.00001322462,0.00008186152,0.003107597,0.0005342074,0.006017439],"genre_scores_gemma":[0.9681427,0.0002105148,0.02938899,0.00004126421,0.000004917655,0.00002654884,0.001285196,0.00002747075,0.0008722603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4859749,"threshold_uncertainty_score":0.9776738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02088933117176308,"score_gpt":0.191111613996836,"score_spread":0.1702222828250729,"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."}}