{"id":"W2807893173","doi":"10.7717/peerj.4850","title":"What killed Frame Lake? A precautionary tale for urban planners","year":2018,"lang":"en","type":"article","venue":"PeerJ","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Northwest Territories; Wilfrid Laurier University; Geological Survey of Canada; Carleton University","funders":"Natural Resources Canada; University of Toronto; Natural Sciences and Engineering Research Council of Canada; Queen's University; Queen's University Belfast; Tides Canada; Royal Bank of Canada; Polar Knowledge Canada","keywords":"Urbanization; Bioindicator; Water quality; Environmental remediation; Environmental science; Hydrology (agriculture); Physical geography; Geography; Contamination; Geology; Ecology","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":[0.003179447,0.000940722,0.0005151206,0.001175142,0.0168024,0.007297705,0.002425898,0.006153135,0.01223969],"category_scores_gemma":[0.007088352,0.0004609889,0.0004390334,0.0008962068,0.008228588,0.009082483,0.00927009,0.008513883,0.001788433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008946855,"about_ca_system_score_gemma":0.02835802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08630518,"about_ca_topic_score_gemma":0.2296774,"domain_scores_codex":[0.998211,0.0007155722,0.00006755559,0.0001431421,0.0002588604,0.0006039136],"domain_scores_gemma":[0.9953021,0.0005971316,0.0002201313,0.0001467251,0.0009941005,0.002739953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009657509,0.0001846249,0.007280054,0.0004030329,0.00002470353,0.001908455,0.03071034,0.0003015939,0.001137206,0.03189426,0.7784696,0.1475896],"study_design_scores_gemma":[0.00001222889,0.0001231699,0.004043762,0.000880826,0.0000205811,0.000397596,0.1239104,0.0001963599,0.0004355744,0.01796803,0.8519257,0.00008578133],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01386017,0.006871564,0.001702667,0.953724,0.004789797,0.0001001291,0.0001488634,0.0001831018,0.01861985],"genre_scores_gemma":[0.4362808,0.03452478,0.02466798,0.3589613,0.005633334,0.0004997213,0.0005984854,0.0003828608,0.1384508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08630518,"threshold_uncertainty_score":0.1716056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01363144512120915,"score_gpt":0.2593580886013178,"score_spread":0.2457266434801086,"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."}}