{"id":"W2139925025","doi":"10.1051/e3sconf/20130135007","title":"Exploring the Relationship between Surface and Subsurface Soil Concentrations of Heavy Metals using Geographically Weighted Regression","year":2013,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario; University of Victoria","funders":"Partenariat Canadien Contre Le Cancer","keywords":"Geographically Weighted Regression; Environmental science; Regression analysis; Soil science; Horizon; Spatial analysis; Environmental chemistry; Statistics; Chemistry; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001447816,0.0004414273,0.0003901061,0.001768236,0.0002294977,0.0007297245,0.0005856203,0.000313777,0.001145986],"category_scores_gemma":[0.005535747,0.000137925,0.0007136199,0.003664149,0.0002154289,0.0004495174,0.0006070255,0.000383906,0.0003642253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004316877,"about_ca_system_score_gemma":0.0006107704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1144738,"about_ca_topic_score_gemma":0.08577576,"domain_scores_codex":[0.9988525,0.0004558134,0.00007479674,0.0003406928,0.0001700123,0.0001062003],"domain_scores_gemma":[0.9972003,0.001628591,0.0004229308,0.0002515076,0.0004326493,0.00006397906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001040061,0.00004650645,0.9396167,0.00005704223,0.00063245,0.0001833485,0.0002383724,0.02513872,0.001983139,0.0006857871,0.001019936,0.03029389],"study_design_scores_gemma":[0.00001105115,0.00009333644,0.8428355,0.00002321434,0.000202237,0.0001485694,0.0009756361,0.1486786,0.001599294,0.001249875,0.004151547,0.00003115322],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783204,0.0001760018,0.01702929,0.0001060043,0.000007803393,0.00001783765,0.003079885,0.0001449526,0.001117839],"genre_scores_gemma":[0.9906474,0.00005822159,0.005357738,0.00001166962,0.000004761723,0.00001391486,0.003201579,0.00002680814,0.000677814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1144738,"threshold_uncertainty_score":0.227615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1271834225613226,"score_gpt":0.2868645486505568,"score_spread":0.1596811260892343,"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."}}