{"id":"W4309162880","doi":"10.1039/d2lc00798c","title":"Ultrathroughput immunomagnetic cell sorting platform","year":2022,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sorting; Computer science; Computational biology; Chemistry; Biology; Algorithm","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":[0.00009093818,0.0001238167,0.000113926,0.00006194427,0.0001654244,0.00002249987,0.0001948945,0.00004864069,0.0001815742],"category_scores_gemma":[0.00001122419,0.0001206367,0.00004539527,0.0001728782,0.00002728003,0.00002977431,0.00007967409,0.0003264598,0.00008158976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006914724,"about_ca_system_score_gemma":0.000009961784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001314552,"about_ca_topic_score_gemma":0.000001227786,"domain_scores_codex":[0.9993262,0.000008192556,0.0001564741,0.0001381047,0.0001219588,0.0002490302],"domain_scores_gemma":[0.9996687,0.00002841578,0.00002600131,0.0002519088,0.000005678481,0.00001928912],"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":[0.0000236357,0.00008552823,0.0002642558,0.00007191031,0.00002137329,0.00006494996,0.0008236272,0.001538419,0.9399258,0.002631492,0.0252381,0.02931094],"study_design_scores_gemma":[0.001100427,0.0006809827,0.001365095,0.00003910958,0.00002778035,0.0001019402,0.002383882,0.005881109,0.8349597,0.002983763,0.149623,0.000853251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968531,0.001625035,0.0001112059,0.0001012093,0.0003339913,0.00009400304,0.00001062318,0.001197348,0.02799556],"genre_scores_gemma":[0.9984658,0.000101076,0.0005908663,0.0001504503,0.00003356815,0.00001093654,0.000009641759,0.00002719879,0.0006104637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1243849,"threshold_uncertainty_score":0.491942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01128452866591902,"score_gpt":0.185971559558851,"score_spread":0.174687030892932,"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."}}