{"id":"W4229021993","doi":"10.5539/mas.v16n2p41","title":"Development of A Smart Rescue Communication System for Drowning Personnel","year":2022,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"IoT and GPS-based Vehicle Safety Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arduino; Computer science; Computer security; Global Positioning System; Emergency rescue; Search and rescue; Work (physics); Smart phone; Aeronautics; Telecommunications; Medical emergency; Embedded system; Engineering; Artificial intelligence; Robot; Medicine","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":[0.001206518,0.00008451805,0.0001335034,0.0001145218,0.0007771191,0.00002194176,0.0005079111,0.00001895199,0.000002759756],"category_scores_gemma":[0.000004199801,0.00009208908,0.00002670813,0.0003352371,0.00006784982,0.00006124423,0.0001241683,0.00009478009,0.000003436582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003393278,"about_ca_system_score_gemma":0.0001117811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009483688,"about_ca_topic_score_gemma":0.00001353461,"domain_scores_codex":[0.9989866,0.0000110271,0.0002523425,0.0001751428,0.0003366286,0.0002382324],"domain_scores_gemma":[0.9995292,0.00003021163,0.00004501025,0.0003126759,0.00003816749,0.00004477549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003271945,0.00001904128,0.00002519782,0.000284164,0.00001140396,2.290494e-7,0.03010488,0.08079153,0.8733078,0.003245507,0.00003731612,0.01214019],"study_design_scores_gemma":[0.0002879282,0.00001157796,0.00006955009,0.00002808668,0.000003151551,0.00000261166,0.007820264,0.9357117,0.05448948,0.00004054,0.001396027,0.0001390143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6405602,0.0001453695,0.3521244,0.00002044441,0.0002718336,0.0006878363,0.00001276882,0.0002751227,0.005902097],"genre_scores_gemma":[0.9888237,4.175598e-7,0.01075143,0.000007911983,0.00001246086,0.0003496043,0.000005894204,0.00001593398,0.00003269082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8549202,"threshold_uncertainty_score":0.597705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929490520230775,"score_gpt":0.2162951510203489,"score_spread":0.1970002458180411,"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."}}