{"id":"W2470210262","doi":"10.4155/bio-2016-0144","title":"32Nd International Symposium on Microscale Separations and Bioanalysis (MSB 2016)","year":2016,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioanalysis; Microscale chemistry; Nanotechnology; Chromatography; Chemistry; Materials science; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000178501,0.0001794862,0.0002007699,0.0003838786,0.00007942125,0.00005076915,0.0001719823,0.0000946233,0.0002607507],"category_scores_gemma":[0.00002248517,0.0001317406,0.00009603906,0.000753242,0.0001167251,0.0001633619,0.00004083594,0.00007211234,0.0001083842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001594684,"about_ca_system_score_gemma":0.000009808431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001124656,"about_ca_topic_score_gemma":0.000002212768,"domain_scores_codex":[0.9990209,0.00001522155,0.0003383142,0.0002673311,0.0001776697,0.0001805014],"domain_scores_gemma":[0.9994532,0.00004052389,0.00006207172,0.0002505262,0.0001509315,0.00004275514],"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":[0.00001332937,0.00005480249,0.002608638,0.00001296434,0.000975629,0.000004398392,0.00009661598,0.00003992786,0.8909888,0.006362378,0.01360004,0.08524253],"study_design_scores_gemma":[0.0007696635,0.00007436235,0.002969926,0.00009162302,0.0004342626,0.00001185341,0.00009402585,0.004845681,0.6281992,0.0007680944,0.3609655,0.0007758185],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1025131,0.001763228,0.8399215,0.006627828,0.0007406099,0.0003492689,0.000522412,0.001134706,0.04642744],"genre_scores_gemma":[0.9951901,0.0004284336,0.001036469,0.0001476526,0.0001066446,0.00002614353,0.00006504035,0.00002314188,0.002976372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8926771,"threshold_uncertainty_score":0.5372227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008077275880557976,"score_gpt":0.2335339720744307,"score_spread":0.2254566961938728,"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."}}