{"id":"W4210460336","doi":"10.2196/preprints.18297","title":"A New Approach for Detecting Sleep Apnea Using a Contactless Bed Sensor: Comparison Study (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Polysomnography; Obstructive sleep apnea; Vital signs; Apnea; Computer science; Sleep (system call); Sleep apnea; Medicine; Mean squared error; Remote patient monitoring; Real-time computing; Simulation; Medical emergency; Artificial intelligence; Statistics; Mathematics; Anesthesia","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"],"consensus_categories":[],"category_scores_codex":[0.0004060281,0.0008433027,0.001322879,0.0002300451,0.0001618481,0.0003734563,0.0007233298,0.0004323334,0.0000345201],"category_scores_gemma":[0.0002102692,0.0009541335,0.0003822944,0.000274773,0.00001881458,0.0001318186,0.001123691,0.001401245,0.00002977362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005631264,"about_ca_system_score_gemma":0.00009154688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009758353,"about_ca_topic_score_gemma":0.00006090164,"domain_scores_codex":[0.9965062,0.000104564,0.0009783345,0.001254355,0.0004375779,0.0007189516],"domain_scores_gemma":[0.9979597,0.000336588,0.0002366902,0.0009439141,0.0001322794,0.0003907721],"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":[0.0001351689,0.0002546248,0.02791257,0.002150445,0.001560626,0.00003084362,0.007194913,0.7422832,0.201588,0.00003699805,0.0001472656,0.01670534],"study_design_scores_gemma":[0.001939749,0.0001442793,0.0002627456,0.0001640253,0.000418894,0.00001250095,0.009557546,0.8598937,0.125764,0.0002053945,0.00008109132,0.001555998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2451413,0.0001107416,0.746759,0.000009665442,0.001197248,0.00381348,0.00001826496,0.001227506,0.001722771],"genre_scores_gemma":[0.7833015,0.000001430808,0.2150846,0.000009332054,0.001067367,0.0002570938,0.00002245499,0.0002315416,0.00002468857],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5381602,"threshold_uncertainty_score":0.9992909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07620532032116535,"score_gpt":0.30197681924653,"score_spread":0.2257714989253646,"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."}}