{"id":"W2904088102","doi":"10.1039/c8lc00938d","title":"On-chip refractive index cytometry for whole-cell deformability discrimination","year":2018,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôpital Maisonneuve-Rosemont; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Cytometry; Index (typography); Refractive index; Chip; Flow cytometry; Optoelectronics; Optics; Materials science; Computer science; Telecommunications; Biology; Physics; Molecular biology; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003685624,0.0004485558,0.000413801,0.0004304274,0.0001782652,0.0004483615,0.0006509362,0.0005622245,0.002053351],"category_scores_gemma":[0.0005317281,0.000180559,0.0002889082,0.0002110913,0.0002803553,0.0004167747,0.0004522406,0.000420804,0.0006985235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000421411,"about_ca_system_score_gemma":0.000330313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006594559,"about_ca_topic_score_gemma":0.001612861,"domain_scores_codex":[0.9996516,0.00004920463,0.0000182264,0.000112533,0.0001337419,0.00003480958],"domain_scores_gemma":[0.9996321,0.0001545157,0.00005740557,0.00006430332,0.00006762436,0.00002403715],"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":[0.00004124342,0.00004346426,0.0003732757,0.00005955779,0.000009526965,0.00002379043,0.00001398037,0.0007720313,0.9855316,0.0004119784,0.0002108432,0.01250881],"study_design_scores_gemma":[0.00000912107,0.0001138432,0.001599611,0.000005439432,0.00001813789,0.00009866514,0.00001439796,0.02874467,0.9657713,0.0001913082,0.003410059,0.00002338325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4400557,0.002427702,0.5443001,0.0003535495,0.0003583712,0.000324033,0.001052268,0.002434104,0.008694133],"genre_scores_gemma":[0.7242746,0.001635323,0.2679346,0.0003703519,0.00007906859,0.0002986263,0.0005835756,0.0001071796,0.004716748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002053351,"threshold_uncertainty_score":0.006869137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01620456012075891,"score_gpt":0.2445508549143629,"score_spread":0.228346294793604,"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."}}