{"id":"W3111335965","doi":"10.1007/978-3-030-57566-3_3","title":"Wearable Technology for Presumptive Diagnosis of High Blood Pressure Based on Risk Factors","year":2020,"lang":"en","type":"book-chapter","venue":"Smart innovation, systems and technologies","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Wearable computer; Blood pressure; Risk analysis (engineering); Medicine; Computer science; Business; Internal medicine; Embedded system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0006486353,0.0005078249,0.001520362,0.001586313,0.0002082845,0.00003191772,0.0002198508,0.001932633,0.0000157332],"category_scores_gemma":[0.001604937,0.000401573,0.0001078264,0.0006239959,0.0002887025,0.0000616365,0.00008313252,0.0009124437,0.00000387213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000565369,"about_ca_system_score_gemma":0.0006658267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001382555,"about_ca_topic_score_gemma":0.00003172144,"domain_scores_codex":[0.9970524,0.00003662839,0.001354836,0.0007631871,0.0004113181,0.0003816027],"domain_scores_gemma":[0.9960862,0.0003943101,0.001335117,0.0008223844,0.001290288,0.00007163966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000142656,0.0001240859,0.04744637,0.01110848,0.001154207,0.0000107078,0.00009468933,0.00001379808,0.00002301746,0.9190708,0.006834646,0.01397655],"study_design_scores_gemma":[0.003518921,0.007123974,0.002932126,0.01073497,0.001263114,0.00003251279,0.001410936,0.0004312995,0.002158681,0.02896861,0.9404183,0.001006536],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2227664,0.1849461,0.01248624,0.2062809,0.01261903,0.1036777,0.04097417,0.02394728,0.1923022],"genre_scores_gemma":[0.9850836,0.001349126,0.0005906877,0.0001012871,0.0001723485,0.0008587639,0.0002188692,0.0001085293,0.01151678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9335837,"threshold_uncertainty_score":0.9998436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03742374193005601,"score_gpt":0.2803351701433559,"score_spread":0.2429114282132999,"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."}}