{"id":"W2909461162","doi":"10.1016/b978-0-12-814130-4.00007-5","title":"Nanoparticles as Biosensors for Food Quality and Safety Assessment","year":2019,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Food safety; Food quality; Instrumentation (computer programming); Scope (computer science); Food industry; Risk analysis (engineering); Biosensor; Nanotechnology; Quality (philosophy); Biochemical engineering; Engineering; Business; Systems engineering; Computer science; Food science; Materials science; Chemistry; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002053342,0.0004668432,0.0006558825,0.00006434409,0.00007510482,0.00004844799,0.000135093,0.0004086075,0.00004757499],"category_scores_gemma":[0.00001735706,0.0004217476,0.0002256211,0.00001022077,0.00008627311,0.00002543779,0.00005094823,0.0003594363,0.00006022997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000122248,"about_ca_system_score_gemma":0.00004104012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.654724e-7,"about_ca_topic_score_gemma":0.00001457929,"domain_scores_codex":[0.9983559,0.00001692122,0.0005441254,0.0004284564,0.000234454,0.0004201614],"domain_scores_gemma":[0.9991081,0.0001939837,0.0001078603,0.0003647582,0.00006552367,0.0001597741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000812525,0.00001227609,0.00001318804,0.0008670859,0.0004837372,0.000004553247,0.00007703389,0.00001358174,0.09112368,0.04519615,0.0001968833,0.8619306],"study_design_scores_gemma":[0.0006249524,0.0002957224,0.00008120704,0.0002161132,0.0001307073,0.00001238042,0.000008757546,0.0001163207,0.03441634,0.0120013,0.9512753,0.0008209168],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04365464,0.001126781,0.000006523206,0.00009229885,0.0002584948,0.001027245,0.0002123412,0.0002364726,0.9533852],"genre_scores_gemma":[0.07887139,0.0004354054,0.001132884,0.0002583851,0.0003767498,0.00002995661,0.00005289806,0.0001955974,0.9186468],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9510784,"threshold_uncertainty_score":0.9998235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01817433932851572,"score_gpt":0.2577533535920214,"score_spread":0.2395790142635057,"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."}}