{"id":"W2392025208","doi":"10.1021/acs.est.6b00361","title":"Development of an in Situ NMR Photoreactor To Study Environmental Photochemistry","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Krembil Foundation; Canada Foundation for Innovation; Government of Ontario","keywords":"Environmental remediation; Pollutant; Environmental chemistry; Chemistry; In situ; Nuclear magnetic resonance spectroscopy; Spectroscopy; Human decontamination; Environmental science; Groundwater; Contamination; Photochemistry; Waste management; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002643099,0.0001964055,0.0002349184,0.0003491054,0.000150703,0.000012186,0.0008650552,0.000117587,0.0007208426],"category_scores_gemma":[0.00002650208,0.0001550203,0.00003185715,0.0004367137,0.0007808447,0.0001817911,0.000404526,0.0001288998,0.00005864274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006478464,"about_ca_system_score_gemma":0.00005402727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000550318,"about_ca_topic_score_gemma":0.00001649629,"domain_scores_codex":[0.9979893,0.000006776585,0.0003693698,0.0007017542,0.0004891223,0.0004436602],"domain_scores_gemma":[0.9991889,0.00001116183,0.0001238801,0.0005227989,0.000002065686,0.0001512178],"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":[0.00001299442,0.0008709793,0.05441874,0.000002453082,0.000008212018,0.0000107429,0.0004846403,0.000001236004,0.8675779,7.098767e-7,3.096851e-7,0.07661105],"study_design_scores_gemma":[0.0005275168,0.00006338152,0.01170461,0.00002338507,0.000008368008,0.000008294518,0.004437731,0.000008133078,0.9822045,0.00001294219,0.0007894278,0.0002116833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988717,0.00002193294,0.00002898199,0.00004560755,0.00001015396,0.00003694472,0.00001395188,0.00005566591,0.0009150597],"genre_scores_gemma":[0.9975639,0.000004020052,0.001972231,0.00001503668,0.000009843206,0.00007583286,0.000004011821,0.00001326052,0.000341843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1146266,"threshold_uncertainty_score":0.7892721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005884372987698797,"score_gpt":0.2247992751106829,"score_spread":0.2189149021229841,"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."}}