{"id":"W4383820935","doi":"10.36227/techrxiv.23614296.v1","title":"Multi-resolution Time-frequency Spectral Derivative Spike Detection for Episode Onset Detection using Passively Collected Sensor Data","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Cardiorespiratory fitness; Heart rate variability; Wearable computer; Sleep (system call); Medicine; Rating scale; Audiology; Statistics; Computer science; Physical therapy; Mathematics; Internal medicine; Heart rate","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":[0.001274129,0.000611273,0.0005629695,0.001956242,0.0001980512,0.0005460006,0.000449215,0.0004322166,0.002891168],"category_scores_gemma":[0.004550887,0.0001850806,0.0006121187,0.001703433,0.0001520981,0.0004208036,0.000457278,0.0003593916,0.0008006128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001677946,"about_ca_system_score_gemma":0.0003157492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001491012,"about_ca_topic_score_gemma":0.002643167,"domain_scores_codex":[0.9993869,0.0001507393,0.00007057132,0.0001794328,0.000151363,0.00006092721],"domain_scores_gemma":[0.9987757,0.0004828457,0.0001576124,0.0002107225,0.0003262757,0.00004691965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002573019,0.0009638869,0.2299656,0.001421188,0.0006705672,0.001024715,0.001213266,0.01796374,0.1780533,0.002175043,0.007961212,0.5560144],"study_design_scores_gemma":[0.0001893506,0.000949427,0.5567161,0.00009621914,0.0002588649,0.00123476,0.0003979051,0.3876006,0.03930805,0.002839968,0.01026853,0.000140217],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6404737,0.0004567218,0.3459174,0.00009841431,0.0001246827,0.0009041108,0.008057469,0.002072149,0.001895513],"genre_scores_gemma":[0.8127369,0.0001479086,0.1794152,0.00004336001,0.00005649121,0.0009621322,0.005743979,0.0001502659,0.0007437015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002891168,"threshold_uncertainty_score":0.009671986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09321385245514051,"score_gpt":0.2963999672321547,"score_spread":0.2031861147770141,"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."}}