{"id":"W2999157192","doi":"10.1149/1945-7111/ab67a5","title":"Review—Graphene-Based Water Quality Sensors","year":2020,"lang":"en","type":"article","venue":"Journal of The Electrochemical Society","topic":"Graphene research and applications","field":"Materials Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Graphene; Robustness (evolution); Computer science; Process engineering; Nanotechnology; Environmental science; Materials science; Chemistry; 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":[0.0007741291,0.00009476139,0.0002296685,0.000005416261,0.0001470082,0.00002865763,0.0005820214,0.00005024996,0.0002038316],"category_scores_gemma":[0.0002226796,0.00004693486,0.0006450642,0.0002491648,0.0001230154,0.00005765941,0.00006575294,0.0003876541,0.0000273597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006339226,"about_ca_system_score_gemma":0.00009298068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002435926,"about_ca_topic_score_gemma":1.937918e-7,"domain_scores_codex":[0.9985676,0.0001402793,0.0003908011,0.0001297483,0.0004593553,0.0003122326],"domain_scores_gemma":[0.9991313,0.00008425653,0.0001865568,0.0001862791,0.0002018992,0.0002097493],"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":[0.00002139719,0.00003255485,0.00007830163,0.0001131567,0.00001389169,1.803281e-7,0.00004252463,0.000001379136,0.9768551,0.00006011687,0.02276086,0.00002051843],"study_design_scores_gemma":[0.0002135162,0.00004258632,0.00004969988,0.00007083793,0.00002702665,0.000005605095,0.00002059259,0.00004902377,0.9873655,0.0009145714,0.01117128,0.00006978399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8527897,0.004651124,0.008371989,0.1336818,0.00006594568,0.0002757462,0.000007407491,0.00003525457,0.0001210374],"genre_scores_gemma":[0.9736763,0.001175245,0.006073196,0.01868841,0.000338236,0.00000900091,0.000002442968,0.00001429067,0.0000229306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1208865,"threshold_uncertainty_score":0.2231813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02876100517209334,"score_gpt":0.3081896748107085,"score_spread":0.2794286696386152,"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."}}