{"id":"W2579041990","doi":"10.1007/s11517-016-1605-7","title":"Smartphone-based colorimetric ELISA implementation for determination of women’s reproductive steroid hormone profiles","year":2017,"lang":"en","type":"article","venue":"Medical & Biological Engineering & Computing","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Computer science; Field (mathematics); Instrumentation (computer programming); Biology; Mathematics; Operating 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003514969,0.000760634,0.0006292099,0.0005521915,0.0002008607,0.0005197164,0.001101877,0.0007627596,0.00897175],"category_scores_gemma":[0.001221172,0.0003017281,0.0002275765,0.0003036669,0.0001115416,0.0003104497,0.0004731761,0.0003743852,0.004240834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001862105,"about_ca_system_score_gemma":0.000378295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009925946,"about_ca_topic_score_gemma":0.002284012,"domain_scores_codex":[0.9995304,0.00006862828,0.00003332811,0.0001028136,0.0002140099,0.00005080273],"domain_scores_gemma":[0.999375,0.000170965,0.00005212317,0.00006298448,0.0002902322,0.00004858354],"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":[0.002123346,0.0006924997,0.02046639,0.001372631,0.0001878984,0.001627422,0.0006160471,0.0009520872,0.6712159,0.001424519,0.03073143,0.2685898],"study_design_scores_gemma":[0.0003440185,0.002471448,0.03643921,0.0002648699,0.0003242841,0.006201845,0.0006449332,0.07518975,0.7988139,0.001281482,0.07778124,0.0002430138],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5003664,0.004779536,0.4067053,0.00206005,0.002031687,0.001614671,0.009472026,0.03571904,0.03725129],"genre_scores_gemma":[0.8569542,0.001090751,0.1098762,0.001595169,0.0002192631,0.0008811252,0.002218982,0.0002979056,0.0268665],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00897175,"threshold_uncertainty_score":0.0300135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882676886223024,"score_gpt":0.27691183090112,"score_spread":0.2580850620388898,"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."}}