{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002933351,0.001097618,0.0005474996,0.0008060682,0.0001914284,0.001202196,0.0007417564,0.001424057,0.005558237],"category_scores_gemma":[0.0002083212,0.0004554046,0.0003343433,0.0006049746,0.0003600655,0.001310313,0.0006111096,0.001035783,0.005558743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005499958,"about_ca_system_score_gemma":0.0002206789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000647195,"about_ca_topic_score_gemma":0.001341025,"domain_scores_codex":[0.9997095,0.00003047778,0.00001123975,0.00006892119,0.0001634849,0.00001626474],"domain_scores_gemma":[0.99994,0.0000227704,0.000005465505,0.000004683404,0.00002328073,0.000003788254],"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":[0.00006911494,0.0001280997,0.0001251332,0.001556621,0.00003102278,0.0002180118,0.0001154572,0.001312549,0.3453862,0.02924988,0.02320268,0.5986052],"study_design_scores_gemma":[0.000008112107,0.0001569772,0.0003094877,0.0002735332,0.00004648577,0.0007758171,0.00007673664,0.003576572,0.224243,0.01215616,0.7583484,0.00002875534],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02181997,0.4349322,0.183147,0.003051176,0.004897508,0.0001559012,0.0004790072,0.001035345,0.350482],"genre_scores_gemma":[0.05454925,0.1795739,0.06608029,0.001777648,0.0007558758,0.0001473165,0.0004824231,0.0002793888,0.6963539],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005558237,"threshold_uncertainty_score":0.01859409,"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."}}