{"id":"W977128589","doi":"","title":"Can mercury levels in bat species along the St. Lawrence River in Ontario be used as an effective biomarker in assessing ecosystem health","year":2010,"lang":"en","type":"article","venue":"Library and Archives Canada (Government of Canada)","topic":"Bat Biology and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercury (programming language); Ecosystem health; Ecosystem; Biomarker; Environmental science; Ecology; Geography; Biology; Ecosystem services; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0002835414,0.0001526085,0.0001497049,0.000641753,0.0005767505,0.0006276132,0.0003720969,0.0003397015,0.0007642563],"category_scores_gemma":[0.0007140494,0.0001272948,0.00008341065,0.0006253407,0.0003575358,0.0004346274,0.000255375,0.0001273504,0.000225088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003002934,"about_ca_system_score_gemma":0.002161486,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7222711,"about_ca_topic_score_gemma":0.9516172,"domain_scores_codex":[0.999836,0.00002832787,0.000007843637,0.00003711616,0.00005400797,0.00003668133],"domain_scores_gemma":[0.9996351,0.00002688521,0.0001299372,0.00001213546,0.0001509083,0.00004508742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004763368,0.000009251576,0.9830579,0.00005543401,0.00003265306,0.0000343452,0.0006791225,0.0000847439,0.003218442,0.00007401405,0.0004253769,0.01228109],"study_design_scores_gemma":[0.000001440989,0.00002792848,0.9970729,0.00001893569,0.00001574532,0.00002595328,0.0007722259,0.0002172594,0.0004193344,0.00004204418,0.001382063,0.000004033734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931545,0.0006150317,0.0003460243,0.000485052,0.00001101342,0.00001476981,0.0008065492,0.00002343204,0.004543745],"genre_scores_gemma":[0.9966459,0.0004245156,0.0006954434,0.00007356475,0.000004309471,0.000007836624,0.000220787,0.000002734373,0.001924993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2777289,"threshold_uncertainty_score":0.5587291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01351135322370851,"score_gpt":0.1827249330306367,"score_spread":0.1692135798069282,"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."}}