{"id":"W2264133883","doi":"10.1016/j.envpol.2016.01.060","title":"Forensic assessment of polycyclic aromatic hydrocarbons at the former Sydney Tar Ponds and surrounding environment using fingerprint techniques","year":2016,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; Cape Breton University","funders":"Public Works and Government Services Canada; Government of Canada","keywords":"Coal tar; Environmental science; Environmental remediation; tar (computing); Environmental chemistry; Soil water; Sediment; Coal; Contamination; Coal combustion products; Pollution; Estuary; Soil contamination; Mining engineering; Environmental engineering; Waste management; Geology; Oceanography; Chemistry; Ecology; Soil science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.000143682,0.0001471335,0.00009983659,0.000991069,0.000563869,0.0003935822,0.0002301325,0.0002905805,0.0006311821],"category_scores_gemma":[0.00024457,0.0001148576,0.00007765161,0.000486571,0.000288177,0.0002092732,0.0003593454,0.0001729913,0.0001355301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003468417,"about_ca_system_score_gemma":0.0005506717,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01572291,"about_ca_topic_score_gemma":0.05418674,"domain_scores_codex":[0.9998803,0.00001443346,0.000004127148,0.00001789681,0.00006659837,0.00001653315],"domain_scores_gemma":[0.9998711,0.00001677399,0.00002985372,0.00000621378,0.00006036037,0.00001569175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002701973,0.000112595,0.4554134,0.0001082719,0.00003940216,0.001632021,0.002401739,0.001177408,0.4812356,0.0005789133,0.0003813163,0.05664903],"study_design_scores_gemma":[0.000009508042,0.000373112,0.8237795,0.00005625472,0.00005607768,0.002250981,0.006252277,0.009329619,0.1541447,0.0004135305,0.003312969,0.00002145754],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977058,0.00004981717,0.0007843215,0.00001452874,0.000002157795,0.000009388836,0.00005176882,0.000007458397,0.001374832],"genre_scores_gemma":[0.9962924,0.0001051036,0.001785987,0.00001133748,0.000002045825,0.000003628887,0.00003566194,0.000001984843,0.001761756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9842771,"threshold_uncertainty_score":0.03126276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082521296384688,"score_gpt":0.2389660769573325,"score_spread":0.2281408639934856,"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."}}