{"id":"W2909208769","doi":"10.4095/295559","title":"Lake sediment grab sampling versus coring for environmental risk assessment of metal mining","year":2014,"lang":"en","type":"report","venue":"","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Coring; Sediment; Sampling (signal processing); Environmental science; Geology; Hydrology (agriculture); Engineering; Geomorphology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00222524,0.0007558747,0.0004897682,0.001867678,0.0004389378,0.0007998035,0.0003674202,0.000218234,0.001525383],"category_scores_gemma":[0.00227008,0.0002133482,0.0003000849,0.002137842,0.0002593639,0.0003677552,0.0004075042,0.0001389884,0.0003804588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009734798,"about_ca_system_score_gemma":0.001127355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04905478,"about_ca_topic_score_gemma":0.1851922,"domain_scores_codex":[0.9977551,0.0009154709,0.0001789754,0.0003259174,0.0006860546,0.0001384965],"domain_scores_gemma":[0.9984568,0.0003277412,0.0003284446,0.0001175382,0.0007035784,0.00006592589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002263149,0.0003428218,0.6634063,0.0005083958,0.0002062978,0.0002725505,0.0007441647,0.005216231,0.08010466,0.0003089997,0.000658765,0.2459676],"study_design_scores_gemma":[0.00008186613,0.003623969,0.9175483,0.0000815829,0.0002568267,0.0003174646,0.001270062,0.01574683,0.05452517,0.0002576536,0.006227744,0.00006258269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9655419,0.0007891656,0.02166187,0.00008100059,0.00002289783,0.0008804447,0.001686812,0.0002642799,0.009071629],"genre_scores_gemma":[0.9493739,0.0006478771,0.04513941,0.00005009407,0.00001271647,0.0002609716,0.001046195,0.00003576397,0.003433106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04905478,"threshold_uncertainty_score":0.09753847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07405126094135613,"score_gpt":0.3464751729103635,"score_spread":0.2724239119690074,"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."}}