{"id":"W2792903264","doi":"10.3390/diseases6010020","title":"Toward Generating More Diagnostic Features from Photoplethysmogram Waveforms","year":2018,"lang":"en","type":"article","venue":"Diseases","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"BC Children's Hospital; Children's Hospital Foundation","keywords":"Photoplethysmogram; Waveform; SIGNAL (programming language); Pulse (music); Wearable computer; Computer science; Medicine; Wearable technology; Artificial intelligence; Telecommunications; Embedded 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":[0.00001961966,0.0002132776,0.0001667032,0.00005388773,0.0001061606,0.0001028303,0.0001854564,0.00006327336,0.0001211368],"category_scores_gemma":[0.000306376,0.000189052,0.00009102173,0.00014784,0.00007778722,0.0001789851,0.00005979653,0.0001078468,0.0001129742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006305321,"about_ca_system_score_gemma":0.00001537576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001628176,"about_ca_topic_score_gemma":0.00001985229,"domain_scores_codex":[0.9990764,0.00001217462,0.0001503394,0.000226262,0.0002035249,0.0003313177],"domain_scores_gemma":[0.999244,0.0002358548,0.00002230107,0.0002615132,0.00004776741,0.0001885613],"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":[0.00004876512,0.0002293849,0.3969262,0.000342861,0.0005115139,0.0004754689,0.004088039,0.003779303,0.4731758,0.0001565078,0.02306725,0.09719885],"study_design_scores_gemma":[0.0009946146,0.0001637331,0.3657694,0.0003948078,0.0002248423,0.00001025002,0.001025756,0.003066281,0.6220692,0.002110698,0.002737329,0.001433073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931379,0.00263137,0.001452012,0.00002402837,0.001168709,0.0001791501,0.0002102511,0.0006349859,0.0005616018],"genre_scores_gemma":[0.9957911,0.00005605999,0.001358801,0.00009743067,0.002438691,0.00007190372,0.0001016589,0.00006034813,0.00002398255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1488933,"threshold_uncertainty_score":0.7709317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01067285599947893,"score_gpt":0.2284017678314844,"score_spread":0.2177289118320055,"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."}}