{"id":"W3027394941","doi":"10.1002/smll.202070112","title":"Single Droplet Detection: A Counter Propagating Lens‐Mirror System for Ultrahigh Throughput Single Droplet Detection (Small 20/2020)","year":2020,"lang":"en","type":"article","venue":"Small","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Lens (geology); Throughput; Excitation; Microfluidics; Numerical aperture; Optics; Aperture (computer memory); Materials science; Field (mathematics); Optoelectronics; Nanotechnology; Physics; Computer science; Acoustics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003108253,0.0004018415,0.000390006,0.0001121049,0.0002278631,0.0001195567,0.0002328795,0.0002630368,0.00002023379],"category_scores_gemma":[0.00009604428,0.000422523,0.0001335667,0.00081113,0.00007244259,0.0002399393,0.00005434567,0.0003725183,0.00004615059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005674449,"about_ca_system_score_gemma":0.00003443959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003428541,"about_ca_topic_score_gemma":0.00004286533,"domain_scores_codex":[0.998024,0.00003597103,0.0007120821,0.0005185729,0.0001991274,0.0005102018],"domain_scores_gemma":[0.998986,0.00005618698,0.000190554,0.0003020893,0.0003977894,0.00006738914],"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":[0.00005888054,0.0000371715,0.00002225218,0.0007684361,0.00006203949,0.00001066391,0.0005665777,0.00004529837,0.9854399,0.0002600758,0.0005938842,0.01213485],"study_design_scores_gemma":[0.0006345449,0.0005547246,0.00002257452,0.0001421941,0.0000523261,0.00008767306,0.0004936587,0.01042756,0.9429106,0.0000474134,0.04414914,0.0004776139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.184427,0.0001313855,0.808601,0.0002303421,0.0008973248,0.001138121,0.00008360764,0.002024475,0.0024668],"genre_scores_gemma":[0.9899413,0.000003810619,0.008420841,0.0003536036,0.0006412553,0.0002586221,0.0001094693,0.0001454371,0.000125672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8055143,"threshold_uncertainty_score":0.9998227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0329981585086664,"score_gpt":0.2136512609610874,"score_spread":0.180653102452421,"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."}}