{"id":"W2999211382","doi":"10.1109/bibe.2019.00094","title":"Needle Optimization for Wrist-Based Electronic Mosquito Pilot Human Testing","year":2019,"lang":"en","type":"article","venue":"","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Diabetes mellitus; Blood testing; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004897747,0.0004162528,0.0004045247,0.0002601458,0.0001341153,0.0003568116,0.0005340063,0.0004459041,0.002441491],"category_scores_gemma":[0.00130993,0.0001190077,0.0002834401,0.0001784249,0.0002163571,0.0004120761,0.0003388045,0.0002155055,0.0004580076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001299116,"about_ca_system_score_gemma":0.0001654955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003848407,"about_ca_topic_score_gemma":0.0004318949,"domain_scores_codex":[0.9995624,0.0001169088,0.00002783716,0.0000657135,0.0001822102,0.00004485291],"domain_scores_gemma":[0.9995074,0.0001718631,0.0000746306,0.00007360773,0.0001225683,0.00004986161],"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":[0.002254117,0.001149047,0.01059859,0.0007872208,0.00008341072,0.001114384,0.0003105667,0.01360719,0.7032541,0.001372446,0.00284543,0.2626236],"study_design_scores_gemma":[0.0004546105,0.03568718,0.04406241,0.0001456521,0.0002513355,0.004383078,0.0003916114,0.1613002,0.7249413,0.001148215,0.02702548,0.0002090013],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7577426,0.001386984,0.2327346,0.0002857161,0.0002848828,0.0006312651,0.0003476849,0.001528135,0.005058082],"genre_scores_gemma":[0.9375414,0.0003254401,0.05942459,0.0001060773,0.00002645687,0.0001021673,0.0001571325,0.00006663053,0.002250172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002441491,"threshold_uncertainty_score":0.008167624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04881651241387382,"score_gpt":0.3240522866627088,"score_spread":0.275235774248835,"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."}}