{"id":"W4205748894","doi":"10.1039/d1ra08264g","title":"Detection of free chlorine in water using graphene-like carbon based chemiresistive sensors","year":2022,"lang":"en","type":"article","venue":"RSC Advances","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Global Water Futures; Canada First Research Excellence Fund","keywords":"Chlorine; Detection limit; Graphene; Tap water; Adsorption; Chemistry; Parts-per notation; Aqueous solution; Seawater; Materials science; Nanotechnology; Chemical engineering; Chromatography; Environmental science; Organic chemistry; Environmental engineering","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":[0.00008687065,0.0001261784,0.0002076504,0.00006680002,0.00005034253,0.000002524863,0.000131243,0.00004114143,0.0001161173],"category_scores_gemma":[0.0000698638,0.000114389,0.00007427652,0.0002453694,0.00004870819,0.00005112039,0.00007321902,0.0002243665,4.81751e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001116757,"about_ca_system_score_gemma":0.000008083702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009715157,"about_ca_topic_score_gemma":0.00001238018,"domain_scores_codex":[0.9990848,0.00001784119,0.0002351272,0.0002169272,0.0002181807,0.0002271527],"domain_scores_gemma":[0.9996156,0.00007283511,0.00004875229,0.0001919576,0.0000252026,0.00004564772],"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":[0.0001001161,0.00003539662,0.0004299077,0.00007161122,0.00001050203,0.00001210723,0.00006054718,0.1442156,0.8549578,0.00001290746,4.676047e-7,0.00009303317],"study_design_scores_gemma":[0.0003622078,0.00001816821,0.0000419039,0.00001401712,0.00001530285,0.000002429855,0.0001694369,0.1354999,0.8630799,0.0001774589,0.000486408,0.0001328629],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983706,0.0001756633,0.0004903402,0.00002738911,0.0000743029,0.00005155355,0.000009861916,0.00004148377,0.0007588253],"genre_scores_gemma":[0.9995105,0.000006324875,0.0002496745,0.00001357851,0.00004416468,0.00001138988,0.000008447924,0.00001591595,0.000139987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00871576,"threshold_uncertainty_score":0.4664648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01095318625239415,"score_gpt":0.2237318625144972,"score_spread":0.2127786762621031,"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."}}