{"id":"W3016970636","doi":"10.1002/smll.201907534","title":"A Counter Propagating Lens‐Mirror System for Ultrahigh Throughput Single Droplet Detection","year":2020,"lang":"en","type":"article","venue":"Small","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Microfluidics; Microscale chemistry; Throughput; Detector; Materials science; Lens (geology); Optoelectronics; Nanotechnology; Realization (probability); Channel (broadcasting); Fluorescence; Optics; Computer science; Physics; Telecommunications","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":[0.0001366118,0.0001517429,0.0001588216,0.00004308142,0.00007135881,0.00003429919,0.00009915406,0.00009258292,0.000007117394],"category_scores_gemma":[0.00003607722,0.000151154,0.00004569127,0.0003044551,0.00002596713,0.0001135818,0.00001644631,0.0001346413,0.00002174657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001725098,"about_ca_system_score_gemma":0.00001245406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000873005,"about_ca_topic_score_gemma":0.000001675221,"domain_scores_codex":[0.9992097,0.000008734582,0.0002935369,0.0001923872,0.00008262661,0.0002130132],"domain_scores_gemma":[0.9996253,0.00001952137,0.00005758986,0.0001186297,0.0001570443,0.00002191674],"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":[0.00001616906,0.000007511871,0.00001679215,0.0004817289,0.00002277514,0.000001844338,0.0003737752,0.00001050689,0.9912359,0.00148019,0.0008094942,0.005543313],"study_design_scores_gemma":[0.0002844411,0.0001444439,0.00002288481,0.00006721985,0.00001427918,0.00001224566,0.0002536145,0.006708461,0.9676063,0.00003621917,0.02466257,0.0001873119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1141374,0.0000550615,0.8800727,0.0001463086,0.0003433651,0.0005869722,0.00003362378,0.001287701,0.003336946],"genre_scores_gemma":[0.9931189,0.000001147818,0.006174097,0.0002657473,0.0001961458,0.0001103072,0.0000458171,0.00005308488,0.00003474235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8789815,"threshold_uncertainty_score":0.6163881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03859458493286773,"score_gpt":0.2162408975700198,"score_spread":0.177646312637152,"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."}}