{"id":"W3080165937","doi":"10.1016/j.talanta.2020.121521","title":"Evaluation of Mass Sensitive Micro-Array biosensors for their feasibility in multiplex detection of low molecular weight toxins using mycotoxins as model compounds","year":2020,"lang":"en","type":"article","venue":"Talanta","topic":"Mycotoxins in Agriculture and Food","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Multiplex; Zearalenone; Mycotoxin; Chemistry; Biosensor; Chromatography; Microfluidics; Food science; Nanotechnology; Materials science; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005162717,0.0001694045,0.0003043831,0.0000198918,0.00006012751,0.00001152702,0.0001404602,0.0001445432,0.0000126293],"category_scores_gemma":[0.0001431911,0.00007352726,0.0001610257,0.000350784,0.00006029918,0.00008160374,0.00003043466,0.00009854886,0.000001555282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007694512,"about_ca_system_score_gemma":0.00002388956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000118612,"about_ca_topic_score_gemma":0.0003749156,"domain_scores_codex":[0.9985704,0.0001912573,0.0003573855,0.0003446252,0.0003393455,0.0001970133],"domain_scores_gemma":[0.9992123,0.0001106858,0.0002073368,0.00007324496,0.0003287909,0.00006761451],"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":[0.0001520308,0.000119932,0.0008270696,0.00002969783,0.00002756917,7.058247e-7,0.0004999217,0.001210218,0.9959551,0.0000153932,0.000005359528,0.001156972],"study_design_scores_gemma":[0.0004740611,0.0002399487,0.005226844,0.0000366192,0.00004857917,0.000004156668,0.0005792644,0.08379429,0.9090384,0.0003985571,0.0000122217,0.0001470839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978379,0.00005843338,0.0003494368,0.0001422816,0.00004273041,0.0009668891,0.0003124245,0.00002160942,0.0002682716],"genre_scores_gemma":[0.9993009,0.00001138828,0.0004386338,0.00008405843,0.00006330796,0.00001383474,0.00008214543,0.000002002272,0.000003718181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08691675,"threshold_uncertainty_score":0.2998354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0630635888704536,"score_gpt":0.2697547943739066,"score_spread":0.206691205503453,"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."}}