{"id":"W2094062313","doi":"10.1063/1.2772175","title":"Integrating optics and microfluidics for time-correlated single-photon counting in lab-on-a-chip devices","year":2007,"lang":"en","type":"article","venue":"Applied Physics Letters","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Institut National d'Optique","funders":"","keywords":"Microfluidics; Fluorophore; Materials science; Cladding (metalworking); Optoelectronics; Fluorescence; Photon counting; Optics; Silicon; Chip; Planar; Nanotechnology; Photon","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":[0.0002005532,0.0002166798,0.0002395871,0.00003228134,0.00006330157,0.00003459713,0.0001099188,0.0001206935,0.00000467985],"category_scores_gemma":[0.00005686339,0.0002213835,0.00005386171,0.0001938537,0.00006374922,0.00004595251,0.00003070956,0.0003624525,0.00001292497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007179693,"about_ca_system_score_gemma":0.000005418771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007919208,"about_ca_topic_score_gemma":8.536905e-7,"domain_scores_codex":[0.9988814,0.000004049295,0.0003002155,0.0002923298,0.000131913,0.0003901176],"domain_scores_gemma":[0.9990632,0.0006238259,0.00007716446,0.0001374592,0.00002316551,0.00007520763],"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":[0.00004950359,0.00004228218,0.000129159,0.0000747755,0.00002667287,0.000004288443,0.0002160275,0.0009512436,0.9944187,0.003031669,0.00008464148,0.0009710836],"study_design_scores_gemma":[0.0005771729,0.00001423151,0.00002802498,0.00008415707,0.0000321532,0.000001454454,0.0001526964,0.03039641,0.9678648,0.0001720817,0.0003687286,0.0003081567],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741734,0.00001684471,0.02228855,0.0001257612,0.0000280129,0.0001570352,0.000006308229,0.00007299089,0.003131104],"genre_scores_gemma":[0.9954187,0.000001719335,0.002899508,0.001346979,0.0001941909,0.000007569341,0.00004508707,0.00004128036,0.0000449184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02944517,"threshold_uncertainty_score":0.9027756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101002228729906,"score_gpt":0.2129978098365495,"score_spread":0.2028975869635589,"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."}}