{"id":"W2532372041","doi":"10.1002/lom3.10145","title":"A fluorescence‐activated cell sorting subsystem for the Imaging FlowCytobot","year":2016,"lang":"en","type":"article","venue":"Limnology and Oceanography Methods","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Woods Hole Oceanographic Institution; National Science Foundation","keywords":"Cell sorting; Sorting; Plankton; Fluorescence-lifetime imaging microscopy; Microfluidics; Biological system; Fluorescence; Flow cytometry; Biology; Ecology; Computer science; Nanotechnology; Physics; Optics; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009677255,0.001069899,0.001005024,0.001136483,0.0008361437,0.001173484,0.001573798,0.0009744944,0.01241221],"category_scores_gemma":[0.0009364567,0.0005280999,0.0005136134,0.000562571,0.0004234092,0.0006363261,0.0005872586,0.001314906,0.005649581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031758,"about_ca_system_score_gemma":0.001235871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002420837,"about_ca_topic_score_gemma":0.002383367,"domain_scores_codex":[0.9992614,0.00006196028,0.00007012521,0.0002473577,0.0002625351,0.00009649318],"domain_scores_gemma":[0.9994259,0.0001620367,0.00005761533,0.0000827001,0.0001601029,0.0001115869],"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":[0.0003319839,0.00008023945,0.0009334586,0.0001443499,0.00002229544,0.000100736,0.00006380181,0.0003126024,0.9679512,0.001035681,0.004982782,0.02404094],"study_design_scores_gemma":[0.0001370308,0.0002897207,0.00563159,0.000051838,0.00005883259,0.0006134978,0.00002527002,0.02959327,0.8799017,0.0005738346,0.0830209,0.000102514],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09595824,0.000716978,0.8376567,0.0006628172,0.000706163,0.002421366,0.01289962,0.04186835,0.007109709],"genre_scores_gemma":[0.1320862,0.0005352535,0.8305371,0.001199224,0.0002250705,0.004927975,0.010464,0.002630752,0.01739446],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01241221,"threshold_uncertainty_score":0.04152304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0184894594501317,"score_gpt":0.2904017967011538,"score_spread":0.2719123372510222,"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."}}