{"id":"W4285033376","doi":"10.22215/etd/2022-14971","title":"Machine Vision for Patient Monitoring in the Neonatal Intensive Care Unit","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Neonatal intensive care unit; Population; Artificial intelligence; Computer science; Computer vision; Medicine; Pediatrics","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":[0.00102289,0.0004128646,0.0002515595,0.0006215181,0.0003091968,0.00114276,0.0003347736,0.0005897566,0.003958505],"category_scores_gemma":[0.001970811,0.0001564995,0.0003039901,0.0006111457,0.0003284258,0.0006342382,0.0006166421,0.0009834728,0.001902371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005598654,"about_ca_system_score_gemma":0.001023961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007225547,"about_ca_topic_score_gemma":0.0009732186,"domain_scores_codex":[0.9994742,0.0001454183,0.00002222294,0.00008314347,0.0002409963,0.00003392694],"domain_scores_gemma":[0.9994897,0.0002264098,0.00004099789,0.00003203416,0.0001777184,0.00003309958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007302973,0.0001089791,0.001419274,0.000678356,0.0000398138,0.0001029543,0.0004592848,0.01654528,0.01273811,0.04680134,0.03297708,0.8880565],"study_design_scores_gemma":[0.00004436554,0.0005379029,0.01504896,0.00158654,0.00008973289,0.0006330811,0.001065693,0.276959,0.03932707,0.1135749,0.551012,0.0001208625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03671466,0.05750296,0.7868784,0.008232835,0.001897846,0.0003668478,0.0006002507,0.001866502,0.1059396],"genre_scores_gemma":[0.3955435,0.0620848,0.4736755,0.001174802,0.0009446024,0.000526025,0.0009339385,0.0002525576,0.06486423],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003958505,"threshold_uncertainty_score":0.01324248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225682302309768,"score_gpt":0.2728132681189737,"score_spread":0.260556445095876,"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."}}