{"id":"W2562783270","doi":"10.1016/j.bios.2016.12.063","title":"Micro-electromechanical film bulk acoustic sensor for plasma and whole blood coagulation monitoring","year":2016,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics","topic":"Acoustic Wave Resonator Technologies","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Project of Shandong Province Higher Educational Science and Technology Program; Qingdao University of Science and Technology; Natural Science Foundation of Shandong Province; Shandong University of Science and Technology; National Natural Science Foundation of China","keywords":"Coagulation; Materials science; Partial thromboplastin time; Prothrombin time; Biomedical engineering; Acoustics; Surgery; Engineering; Medicine; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.00009550797,0.0002368113,0.0002300864,0.0001036897,0.0001060011,0.00004247211,0.0000888202,0.0002730216,0.000002415926],"category_scores_gemma":[0.0001096476,0.0001789623,0.00004393619,0.0001103304,0.000084194,0.00006793392,0.00003894703,0.0001362289,0.00000415475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008299223,"about_ca_system_score_gemma":0.00001885724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001565497,"about_ca_topic_score_gemma":0.000003323722,"domain_scores_codex":[0.9988244,0.00001010472,0.0002055437,0.0003001428,0.0001093308,0.0005505031],"domain_scores_gemma":[0.999465,0.0002044725,0.00003877857,0.000168391,0.00004464485,0.00007866167],"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":[0.00002126823,0.00001390027,0.000171337,0.00006068744,0.00005850126,0.000003131863,0.0000130727,0.0000711233,0.9782959,0.0002906342,0.000121929,0.02087849],"study_design_scores_gemma":[0.001305073,0.000607509,0.0003499899,0.00008068525,0.0001357713,0.0001138516,0.00007815225,0.05254084,0.9397349,0.0008010357,0.003782089,0.0004701406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908357,0.001768248,0.00596503,0.0002618962,0.0001240952,0.0002828887,0.00006907715,0.000683716,0.000009298124],"genre_scores_gemma":[0.9940047,0.001771669,0.003874191,0.000006049318,0.0001230501,0.00002274448,0.000003305802,0.00006273502,0.0001315381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05246972,"threshold_uncertainty_score":0.7297873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009509304157896732,"score_gpt":0.2088559389558395,"score_spread":0.1993466347979428,"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."}}