{"id":"W4319586960","doi":"10.2196/44575","title":"Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Health and Social Care; National Institute for Health and Care Research","keywords":"Artificial intelligence; Photoplethysmogram; Computer science; Computer vision; Channel (broadcasting); Segmentation; Pattern recognition (psychology); Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007544127,0.0001257203,0.0002334347,0.001386932,0.00004974272,0.00001568301,0.0002362821,0.00007308496,0.000006002606],"category_scores_gemma":[0.00007416795,0.0001243819,0.00006041997,0.003500327,0.0001104086,0.0003219412,0.0001212442,0.0005528388,0.00001126981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021473,"about_ca_system_score_gemma":0.00002824262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001557429,"about_ca_topic_score_gemma":0.0002311422,"domain_scores_codex":[0.9984543,0.0002081918,0.0003791349,0.0001602953,0.000388924,0.0004090938],"domain_scores_gemma":[0.9992996,0.0002299591,0.00005315351,0.0001634341,0.0002040101,0.00004978436],"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":[0.000462186,0.001361973,0.09283845,0.003603365,0.0004803002,0.0001810242,0.1502407,0.0154406,0.5601497,0.000324844,0.001597068,0.1733198],"study_design_scores_gemma":[0.001758871,0.002430062,0.1329279,0.001013974,0.000006918579,0.000009744824,0.01992899,0.04096115,0.7974329,0.003073383,0.00005159293,0.000404479],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973713,0.00004639709,0.0008783563,0.00001077173,0.0001227526,0.001041921,0.000004500361,0.0001056278,0.0004184154],"genre_scores_gemma":[0.9997436,0.00001642127,0.00006022957,3.343507e-7,0.00001914014,0.0000996661,0.000005430168,0.00002980764,0.00002533552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2372832,"threshold_uncertainty_score":0.5072145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07328562655096875,"score_gpt":0.3733194582141399,"score_spread":0.3000338316631712,"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."}}