{"id":"W2134910569","doi":"10.1038/nmeth.1452","title":"Using buoyant mass to measure the growth of single cells","year":2010,"lang":"en","type":"article","venue":"Nature Methods","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":405,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences","keywords":"Microchannel; Yeast; Microfluidics; Chemistry; Bacillus subtilis; Saccharomyces cerevisiae; Biophysics; Single-cell analysis; Chromatography; Cell; Bacteria; Nanotechnology; Materials science; Biology; Biochemistry; Genetics","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":[0.0005863964,0.0009080271,0.0004257981,0.00144158,0.0003523719,0.0008679864,0.0006737473,0.001230678,0.0008667091],"category_scores_gemma":[0.001080229,0.0004007648,0.0003014923,0.0006746469,0.000546347,0.0009250715,0.000586922,0.00103687,0.0008323403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006544068,"about_ca_system_score_gemma":0.00028771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001568447,"about_ca_topic_score_gemma":0.001855893,"domain_scores_codex":[0.9994118,0.00005946875,0.00002785567,0.0001336978,0.0003236911,0.00004341165],"domain_scores_gemma":[0.9991792,0.0003306049,0.0001511499,0.0000634544,0.0001952428,0.00008036059],"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":[0.00002795018,0.00002411997,0.0006660753,0.00004210076,0.000008448418,0.00002131131,0.00006028333,0.0001484623,0.9919858,0.0003195597,0.0001346682,0.006561329],"study_design_scores_gemma":[0.00001129355,0.0001325907,0.004184496,0.000008868245,0.00002168741,0.0001204021,0.00003893672,0.01454374,0.9790158,0.0003548271,0.001540843,0.00002645707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.712528,0.00473671,0.2698969,0.001069421,0.000778175,0.0002839015,0.001289737,0.001105671,0.008311579],"genre_scores_gemma":[0.8133572,0.004011167,0.172812,0.0007142357,0.0003079573,0.0005111439,0.00102881,0.0001494735,0.007108119],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001568447,"threshold_uncertainty_score":0.004748106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03124298320963569,"score_gpt":0.306975106922585,"score_spread":0.2757321237129493,"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."}}