{"id":"W2887892665","doi":"","title":"Development of a microfluidic platform for size-based enrichment and immunomagnetic isolation of circulating tumour cells","year":2017,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; University of Victoria","keywords":"Isolation (microbiology); Microfluidics; Immunomagnetic separation; Nanotechnology; Computational biology; Chromatography; Computer science; Chemistry; Biology; Materials science; Bioinformatics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002592857,0.0002179312,0.0003471339,0.0004230609,0.0001545292,0.00002196116,0.0003553334,0.0002618778,0.00004492998],"category_scores_gemma":[0.0001030868,0.0002649013,0.00009587225,0.0001809198,0.00007854006,0.00008860729,0.0000417416,0.0002063312,0.000002450358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001852218,"about_ca_system_score_gemma":0.0002610341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003557528,"about_ca_topic_score_gemma":0.0005866219,"domain_scores_codex":[0.9988068,0.00001477549,0.000354962,0.0002415327,0.0002967813,0.0002851825],"domain_scores_gemma":[0.9989813,0.0002623194,0.0002448442,0.0002468277,0.0001759621,0.00008874256],"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":[0.0006715942,0.0002128492,0.01822564,0.01359688,0.0006132042,0.00003374896,0.0007478803,0.000491589,0.8693302,0.000146633,0.00170182,0.09422799],"study_design_scores_gemma":[0.002377614,0.0001576891,0.008830229,0.001292621,0.0001759229,5.569877e-9,0.005824904,0.005536533,0.9528951,0.00004229915,0.02227495,0.0005921491],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932726,0.0005919273,0.003390715,0.000003831307,0.0002246123,0.0005077177,0.00003586828,0.00004355824,0.001929183],"genre_scores_gemma":[0.9908859,0.0001301897,0.007487127,0.000001433511,0.0000171159,0.000003887844,0.0002286153,0.00003875595,0.001207013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09363585,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01512314630383356,"score_gpt":0.236056455390617,"score_spread":0.2209333090867835,"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."}}