{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008062476,0.0001782428,0.0003263196,0.0001206742,0.000143237,0.00004249586,0.0002338528,0.0001878032,0.00004309165],"category_scores_gemma":[0.001406614,0.0001485912,0.00009538508,0.0001402466,0.00008108821,0.00006747749,0.00006037207,0.0001983168,0.000004203481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001882673,"about_ca_system_score_gemma":0.00001845716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001642051,"about_ca_topic_score_gemma":0.000001016153,"domain_scores_codex":[0.9986104,0.0000216159,0.0004228168,0.0002957579,0.0002344668,0.000414892],"domain_scores_gemma":[0.9991388,0.0002573442,0.0001211861,0.0002397,0.00008496135,0.0001580635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001785596,0.0002516798,0.009265023,0.0007862583,0.000172679,0.0000134563,0.0004175344,0.01754054,0.2105427,0.0008055465,0.0002600251,0.759766],"study_design_scores_gemma":[0.001044398,0.0004594686,0.1198016,0.00006765554,0.00001650739,0.000003655559,0.00006320208,0.832532,0.04503052,0.00008159287,0.0006181725,0.0002811969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7602018,0.00008973887,0.2388435,0.0000830278,0.0003462357,0.0002449942,0.00001000494,0.0001504859,0.00003017749],"genre_scores_gemma":[0.9932405,0.00001592087,0.006300389,0.00002440131,0.000331728,0.00004388537,0.00002021712,0.00001897547,0.000003993782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8149915,"threshold_uncertainty_score":0.6059373,"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."}}