{"id":"W2964490177","doi":"10.1016/j.cclet.2019.07.045","title":"Nanomaterials for analytical chemistry","year":2019,"lang":"en","type":"article","venue":"Chinese Chemical Letters","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nanomaterials; Nanotechnology; Chemistry; Environmental chemistry; Materials science","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":[0.0008844332,0.001246059,0.000842174,0.001363503,0.001261947,0.001533871,0.00134085,0.001736309,0.01735877],"category_scores_gemma":[0.0007643288,0.0005685206,0.000523905,0.0006290816,0.001230539,0.001779866,0.002402641,0.003327039,0.01753094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001464786,"about_ca_system_score_gemma":0.00115823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00044021,"about_ca_topic_score_gemma":0.0008960744,"domain_scores_codex":[0.9990741,0.0001050773,0.0000420219,0.0001745182,0.000517654,0.00008664919],"domain_scores_gemma":[0.9997429,0.00003575802,0.00001776914,0.00005637374,0.0001145676,0.00003264579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007928713,0.0001395075,0.000272584,0.001360753,0.00005441146,0.000363599,0.0002892193,0.000322052,0.2376672,0.2888517,0.1768659,0.293734],"study_design_scores_gemma":[0.00001132674,0.00007855135,0.0002697748,0.00008389127,0.00001434158,0.0004269075,0.00003554868,0.000667504,0.1134639,0.02919178,0.8557332,0.00002324758],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.01577962,0.1200994,0.2041305,0.02251187,0.02402277,0.0005849673,0.001585393,0.003640629,0.6076449],"genre_scores_gemma":[0.1771918,0.07533357,0.1312428,0.009479453,0.006702658,0.00146629,0.003082112,0.0009737379,0.5945275],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01735877,"threshold_uncertainty_score":0.0580709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146788031961791,"score_gpt":0.272140244270563,"score_spread":0.2606723639509451,"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."}}