{"id":"W4410085765","doi":"10.2196/57469","title":"Enhancing Cardiopulmonary Resuscitation Quality Using a Smartwatch: Neural Network Approach for Algorithm Development and Validation","year":2025,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; NOSM University; Saint Mary's University","funders":"","keywords":"Accelerometer; Artificial neural network; Computer science; Smartwatch; Cardiopulmonary resuscitation; Machine learning; Medicine; Wearable computer; Embedded system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002745993,0.00136536,0.0008260211,0.001214072,0.0004874769,0.00105649,0.001260165,0.001629172,0.001610459],"category_scores_gemma":[0.006959352,0.0005356623,0.0007993573,0.0007948038,0.0003965929,0.0009976997,0.0008600443,0.001775528,0.0003670445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001361185,"about_ca_system_score_gemma":0.001347268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02148605,"about_ca_topic_score_gemma":0.01447921,"domain_scores_codex":[0.9993128,0.0002620533,0.00006821104,0.0001943422,0.00009997663,0.00006269207],"domain_scores_gemma":[0.9972276,0.001784572,0.0001920062,0.0001141834,0.0006304042,0.00005120125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001337954,0.0001863436,0.004381449,0.00006029007,0.00009812399,0.00005088324,0.00004580752,0.8977407,0.001274303,0.0005694182,0.0005786442,0.0948803],"study_design_scores_gemma":[0.000003024109,0.000018173,0.0002392966,0.00000508413,0.000004168413,0.000002908174,0.00000422155,0.9992172,0.0002646256,0.0001956829,0.00004334843,0.000002280615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1499697,0.0008429536,0.8445123,0.0004266886,0.00008959743,0.0003561699,0.0003103366,0.001832034,0.001660086],"genre_scores_gemma":[0.775298,0.0002817128,0.2211701,0.0001710279,0.00003850578,0.0006291893,0.0007034168,0.00007257442,0.001635347],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02148605,"threshold_uncertainty_score":0.04272199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06951357287046808,"score_gpt":0.3939427822011211,"score_spread":0.324429209330653,"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."}}