{"id":"W6990326961","doi":"","title":"Developing an IoT bathroom speaker for elderly safety","year":2024,"lang":"en","type":"other","venue":"DR-NTU (Nanyang Technological University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software; Classifier (UML); Artificial neural network; Precision and recall; Deep learning; Data collection; Noise (video); Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003733907,0.000615863,0.0003935326,0.0003562988,0.0003794553,0.0005862598,0.0008405381,0.000640875,0.005741527],"category_scores_gemma":[0.0006525546,0.0001979915,0.0003393835,0.0001861269,0.0001846773,0.0009604402,0.001124412,0.0005589909,0.003573812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002880723,"about_ca_system_score_gemma":0.0005649258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001528744,"about_ca_topic_score_gemma":0.001890575,"domain_scores_codex":[0.9997361,0.00003481236,0.00001563322,0.00005558799,0.0001190635,0.00003879265],"domain_scores_gemma":[0.9997692,0.00002520763,0.00001742593,0.00002180149,0.0001185767,0.00004788621],"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":[0.001219957,0.0005181907,0.009854445,0.000581666,0.0001088949,0.001507527,0.001104315,0.003438812,0.2829536,0.004166471,0.03177913,0.6627671],"study_design_scores_gemma":[0.0003238807,0.003184207,0.03064056,0.0003900256,0.0005881505,0.004162919,0.002168695,0.3948212,0.334489,0.005446189,0.2234746,0.0003106418],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2157858,0.001523057,0.7138768,0.001496662,0.001162081,0.001227051,0.001147819,0.02296673,0.04081392],"genre_scores_gemma":[0.6380703,0.001181067,0.3096484,0.001198312,0.0003483016,0.0007530858,0.001792124,0.0003218377,0.04668656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005741527,"threshold_uncertainty_score":0.01920736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0370567409335553,"score_gpt":0.2573369907619384,"score_spread":0.2202802498283831,"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."}}