{"id":"W2624962964","doi":"10.21785/icad2017.066","title":"Did You Feel That? Developing Novel Multimodal Alarms for High Consequence Clinical Environments","year":2017,"lang":"en","type":"article","venue":"","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"ALARM; Perception; Haptic technology; Computer science; Human–computer interaction; Audiology; Alarm signal; Speech recognition; Psychology; Medicine; Simulation; Engineering; Neuroscience","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":[0.00142732,0.0003928912,0.0002055942,0.0001677535,0.0002011453,0.0009055967,0.0004772477,0.0007147177,0.003345361],"category_scores_gemma":[0.004880628,0.0001423102,0.0002735153,0.00005810291,0.0002993522,0.0008584163,0.0006910283,0.0004867112,0.0007398811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128583,"about_ca_system_score_gemma":0.0003209041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001173879,"about_ca_topic_score_gemma":0.0003382978,"domain_scores_codex":[0.9996002,0.0001571473,0.00002084708,0.00006252009,0.0001099369,0.0000493235],"domain_scores_gemma":[0.9983401,0.001008563,0.0001636463,0.00005959655,0.0002597927,0.0001682166],"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":[0.00161759,0.00171004,0.02074662,0.001431419,0.0001290398,0.001825023,0.006476338,0.002420105,0.3644713,0.002282237,0.009930721,0.5869596],"study_design_scores_gemma":[0.001212588,0.02961217,0.1202053,0.001330388,0.001538182,0.01995226,0.01935888,0.1378283,0.4811795,0.01241312,0.1746566,0.0007126433],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7261856,0.0007356227,0.257443,0.003331868,0.0005572709,0.000792528,0.0001186602,0.001652869,0.009182581],"genre_scores_gemma":[0.7219951,0.0006227153,0.2691729,0.001522606,0.0001448762,0.0004443929,0.00009921753,0.00009260525,0.005905576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003345361,"threshold_uncertainty_score":0.01119137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2320897653643851,"score_gpt":0.4399780014474173,"score_spread":0.2078882360830322,"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."}}