{"id":"W2081609467","doi":"10.1117/12.417440","title":"Microfluidics in environmental monitoring: toward a shoebox-size spectrometer for measuring mercury in the environment","year":2001,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mercury (programming language); Spectrometer; Computer science; Environmental science; Physics; Optics; Programming language","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001501465,0.000660779,0.0004416982,0.0005750898,0.0005022252,0.001030891,0.001234978,0.001243575,0.001042489],"category_scores_gemma":[0.0007347577,0.0004006359,0.0003224522,0.0004174141,0.000998725,0.00148959,0.000665648,0.001049228,0.0008365602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005685916,"about_ca_system_score_gemma":0.000972436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001085175,"about_ca_topic_score_gemma":0.002345783,"domain_scores_codex":[0.9994259,0.000102598,0.00002728533,0.0001281395,0.0002704568,0.00004571918],"domain_scores_gemma":[0.9996419,0.00008480662,0.00004512507,0.00002637062,0.0001250018,0.0000767099],"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":[0.0001135435,0.000132498,0.000864969,0.0002769827,0.00001448621,0.0001184276,0.0001060935,0.0004798934,0.942196,0.0047121,0.001695757,0.04928928],"study_design_scores_gemma":[0.00006595333,0.0009198395,0.001621376,0.00004934769,0.00003899252,0.0007226089,0.0001654083,0.009193085,0.9383322,0.002504871,0.04630744,0.00007885416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2370041,0.03270965,0.7037101,0.008671347,0.002166766,0.0009278609,0.0004283944,0.002600743,0.01178099],"genre_scores_gemma":[0.2072663,0.01251908,0.762765,0.001750525,0.0004762664,0.0002955156,0.0001738834,0.0001090391,0.01464435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001501465,"threshold_uncertainty_score":0.00794065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01802800033735072,"score_gpt":0.2193378775324408,"score_spread":0.2013098771950901,"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."}}