{"id":"W4386100484","doi":"10.1021/acs.analchem.3c02397","title":"Quantitative and Multiplexed Chopper-Based Time-Gated Imaging for Bioanalysis on a Smartphone","year":2023,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Killam Trusts; University of British Columbia; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Chemistry; Förster resonance energy transfer; Luminescent Measurements; Microsecond; Fluorescence-lifetime imaging microscopy; Autofluorescence; Multiplexing; Luminescence; Fluorescence; Optoelectronics; Computer science; Optics; Materials science; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001210124,0.0001752068,0.0002448869,0.00008742355,0.00007182221,0.00004665423,0.00006286772,0.00009299806,0.000098651],"category_scores_gemma":[0.0002128903,0.0001625963,0.0001451728,0.000553367,0.00007221434,0.00003406015,0.00001373426,0.0001435263,0.000116174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000570949,"about_ca_system_score_gemma":0.000008374628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006747281,"about_ca_topic_score_gemma":0.000001294893,"domain_scores_codex":[0.9990831,0.000007969212,0.0002030544,0.0002767071,0.0001339735,0.0002951658],"domain_scores_gemma":[0.9993325,0.0002898376,0.0000196851,0.0001582332,0.00005320966,0.0001464603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002473147,0.0001117408,0.0006382593,0.0005507579,0.0005325014,0.00003986594,0.00004006222,0.01931757,0.9596447,0.0001234522,0.0105948,0.008158985],"study_design_scores_gemma":[0.0004803377,0.00002329317,0.0002513204,0.00002680773,0.00009476765,8.979828e-7,0.00003391267,0.9106986,0.08704537,0.00008000037,0.001074646,0.0001900328],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897055,0.0001121574,0.003680045,0.002026033,0.00005943346,0.0001895769,0.000129885,0.001061354,0.003035993],"genre_scores_gemma":[0.9981669,0.00001474622,0.0004130325,0.0000891326,0.00005651947,0.00001174628,0.00008673315,0.00003307377,0.001128142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.891381,"threshold_uncertainty_score":0.6630487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340110447589958,"score_gpt":0.2445463544533443,"score_spread":0.2311452499774447,"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."}}