{"id":"W2095513494","doi":"10.1002/elps.200406070","title":"The potential of autofluorescence for the detection of single living cells for label‐free cell sorting in microfluidic systems","year":2004,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Microfluidics; Autofluorescence; Cell sorting; Single-cell analysis; Fluorescence; Fluorescence microscope; Materials science; Flow cytometry; Confocal; Nanotechnology; Microscope; Confocal microscopy; Cell; Microscopy; Biomedical engineering; Chemistry; Cell biology; Biology; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008990917,0.0004471487,0.0004072605,0.000569862,0.0004259132,0.0006781856,0.0007603035,0.0009192041,0.0006775273],"category_scores_gemma":[0.0007583209,0.000306487,0.0003423868,0.0001837066,0.000695955,0.0007773252,0.0004593479,0.0007328057,0.0003295132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005928727,"about_ca_system_score_gemma":0.0005191388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004631714,"about_ca_topic_score_gemma":0.0006741747,"domain_scores_codex":[0.9995976,0.0001046212,0.00002446929,0.00007747854,0.0001559151,0.00004006098],"domain_scores_gemma":[0.9995099,0.0003110598,0.00004159176,0.00004315276,0.00005077108,0.00004355472],"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":[0.00003935628,0.00001783101,0.0001172815,0.00008726427,0.000004282495,0.00006382911,0.00002522477,0.000271855,0.9846079,0.001749131,0.0001238648,0.0128923],"study_design_scores_gemma":[0.00002657452,0.0001830984,0.0005061144,0.00001935638,0.00001646739,0.000515869,0.00001491033,0.007078117,0.9821176,0.001768151,0.007724638,0.0000290694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3436422,0.02157544,0.6273499,0.001797342,0.0005754259,0.000202488,0.00023984,0.001206038,0.003411347],"genre_scores_gemma":[0.5925053,0.01117751,0.3920183,0.0007010444,0.0002520859,0.0003555364,0.0002229195,0.00007248505,0.002694809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009192041,"threshold_uncertainty_score":0.004754901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007027419692245589,"score_gpt":0.1836185708865859,"score_spread":0.1765911511943403,"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."}}