{"id":"W2766427015","doi":"10.1098/rsos.171025","title":"Portable device for the detection of colorimetric assays","year":2017,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Detection limit; Hue; Standard deviation; Colorimetry; Computer science; Relative standard deviation; Reagent; Chemistry; Analytical Chemistry (journal); Biological system; Artificial intelligence; Chromatography; Computer vision; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00110609,0.001946033,0.00115904,0.001679907,0.0004637738,0.0009226315,0.00258914,0.001961275,0.01004879],"category_scores_gemma":[0.002115036,0.0007258913,0.0007076568,0.001117043,0.0004570836,0.0009174065,0.00107966,0.001516477,0.007305634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003658975,"about_ca_system_score_gemma":0.0004516364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000260571,"about_ca_topic_score_gemma":0.0003152842,"domain_scores_codex":[0.9976588,0.0002985132,0.0001290639,0.0006061886,0.001197188,0.0001102662],"domain_scores_gemma":[0.9990545,0.0003153313,0.0001391289,0.0001465913,0.0002913538,0.00005321302],"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":[0.0002966539,0.000292987,0.001110628,0.001978575,0.00008708169,0.000588791,0.0001252458,0.0004559339,0.8383467,0.002495936,0.01594916,0.1382724],"study_design_scores_gemma":[0.0001271543,0.001477557,0.003578624,0.0002592442,0.000214175,0.004594169,0.00009519997,0.00940928,0.8153828,0.001040082,0.1636537,0.000168072],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05229595,0.01245399,0.8888721,0.0007480475,0.003238,0.003338516,0.002910662,0.00945843,0.02668424],"genre_scores_gemma":[0.2088827,0.00808352,0.7231348,0.002008567,0.0006881523,0.005284661,0.003469063,0.000397577,0.04805098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01004879,"threshold_uncertainty_score":0.03361648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02710157872348003,"score_gpt":0.2884415038617932,"score_spread":0.2613399251383132,"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."}}