{"id":"W1973370837","doi":"10.1021/es902409t","title":"In Situ Optical Absorption Mercury Continuous Emission Monitor","year":2009,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Ontario Centres of Excellence","keywords":"Mercury (programming language); In situ; Environmental science; Environmental chemistry; Absorption (acoustics); Remote sensing; Materials science; Chemistry; Optics; Computer science; Physics; Geology","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":[0.0004271776,0.0004108364,0.0003202882,0.0003979446,0.0002904205,0.0003954693,0.0009437383,0.0005041175,0.001480321],"category_scores_gemma":[0.0005969947,0.0002037782,0.0001788756,0.0003093138,0.0002367714,0.0003906566,0.0005097446,0.0005637436,0.0004163817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004056724,"about_ca_system_score_gemma":0.0003489176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009775786,"about_ca_topic_score_gemma":0.001740554,"domain_scores_codex":[0.9990647,0.0001084385,0.00002028759,0.000194124,0.0005654588,0.00004696698],"domain_scores_gemma":[0.9994841,0.0001211164,0.00008303479,0.00005470836,0.0002301725,0.00002678636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001217097,0.0000815021,0.002794656,0.0001204034,0.00001452695,0.00006446462,0.00006547523,0.000677386,0.9726613,0.0002740027,0.0005262156,0.02259845],"study_design_scores_gemma":[0.00001439525,0.0002418511,0.002927846,0.000007531342,0.00002427056,0.0002102271,0.00003826811,0.006285814,0.982717,0.00007774345,0.007439027,0.00001595654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5908255,0.001183027,0.389049,0.0004217917,0.0002462713,0.0003419332,0.001162865,0.003336766,0.01343289],"genre_scores_gemma":[0.8030385,0.00114375,0.1814102,0.0002809856,0.00009479347,0.0002394489,0.0006794606,0.0001440073,0.01296876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001480321,"threshold_uncertainty_score":0.004952133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006774088812198643,"score_gpt":0.2486833648830685,"score_spread":0.2419092760708698,"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."}}