{"id":"W3195469103","doi":"10.1021/acsomega.1c03460","title":"Quantitative Point-of-Care Colorimetric Assay Modeling Using a Handheld Colorimeter","year":2021,"lang":"en","type":"article","venue":"ACS Omega","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Colorimeter; Analyte; Mobile device; Colorimetry; Point of care; Computer science; Chromatography; Chemistry; Biological system","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":[0.00009551756,0.0001109303,0.0002122282,0.0001489478,0.00004862195,0.00003040348,0.0000557832,0.0001045192,0.00001253056],"category_scores_gemma":[0.0001559036,0.0001113633,0.00008766768,0.0007472268,0.00001898516,0.0001149416,0.00002873607,0.0001516699,0.00001621743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000704887,"about_ca_system_score_gemma":0.00002287914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002645184,"about_ca_topic_score_gemma":0.00001279782,"domain_scores_codex":[0.9992886,0.00003094321,0.0002070627,0.0001529635,0.0001380842,0.0001823394],"domain_scores_gemma":[0.999504,0.00009893225,0.00002401909,0.0001347633,0.0001865064,0.00005173559],"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":[0.00008307714,0.00008039724,0.0004950046,0.000514699,0.0003723453,0.00005429908,0.0009052241,0.3199302,0.6664203,0.003378091,0.0002083351,0.00755799],"study_design_scores_gemma":[0.0002212331,0.00007964395,0.00004340933,0.00005285557,0.00006034976,0.000007236005,0.000562601,0.7978808,0.2004147,0.0002391255,0.0002766283,0.0001614106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386337,0.001772827,0.05700136,0.00001763059,0.0003492166,0.00006274664,0.00001183466,0.00008253275,0.002068122],"genre_scores_gemma":[0.9928347,0.0000749738,0.006931623,0.00002148986,0.00005023516,0.000002136043,0.000005731003,0.00002313147,0.00005590387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4779506,"threshold_uncertainty_score":0.4541265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03353860400714585,"score_gpt":0.2647114621139405,"score_spread":0.2311728581067946,"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."}}