{"id":"W1970062918","doi":"10.1134/s1023193514040089","title":"A novel electrochemical noise sensor applied to detect food safety","year":2014,"lang":"en","type":"article","venue":"Russian Journal of Electrochemistry","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Electrochemical noise; Electrochemistry; Noise (video); Food safety; Electrochemical gas sensor; Environmental science; Materials science; Electrode; Computer science; Chemistry; Food science; Artificial intelligence","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":[0.0006038941,0.0009427664,0.000932027,0.0004825736,0.0002234149,0.0005399405,0.001017267,0.001420756,0.0005134774],"category_scores_gemma":[0.0006282059,0.0004484673,0.0004266398,0.0004558666,0.0002979769,0.0007331655,0.0004932717,0.0004488242,0.0005243776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003210041,"about_ca_system_score_gemma":0.0003101116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00026351,"about_ca_topic_score_gemma":0.0003619721,"domain_scores_codex":[0.9990854,0.0001216953,0.000043149,0.0002759768,0.000421699,0.00005210216],"domain_scores_gemma":[0.9997161,0.00006110033,0.00003708164,0.00002260702,0.0001333835,0.00002975845],"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":[0.00005135477,0.00002348284,0.0002601842,0.0001380754,0.00001018718,0.00009855044,0.00001986667,0.0001976921,0.9895533,0.0002018509,0.00011318,0.009332375],"study_design_scores_gemma":[0.00001539654,0.0003539607,0.001016708,0.0000100485,0.00003546782,0.0006182645,0.0000146736,0.01046083,0.9818913,0.0001043702,0.005451695,0.00002718422],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4071004,0.01036112,0.5733668,0.000532791,0.001199782,0.0004200022,0.0005932471,0.00181479,0.004611113],"genre_scores_gemma":[0.7749402,0.002815213,0.2136368,0.0005376376,0.0001551848,0.0002416109,0.000312358,0.00005354631,0.007307437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001420756,"threshold_uncertainty_score":0.003193736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003892561137081977,"score_gpt":0.1871955864663433,"score_spread":0.1833030253292613,"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."}}