{"id":"W4386010826","doi":"10.5267/j.ijdns.2023.7.019","title":"Internet of Things: Underwater routing based on user’s health status for smart diving","year":2023,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Underwater; Routing (electronic design automation); Path (computing); Shortest path problem; The Internet; Internet of Things; Computer science; Everyday life; Computer security; Computer network; World Wide Web; Geography","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":[0.001681818,0.00006138437,0.0001262493,0.0001578288,0.00006410898,0.00011955,0.001020507,0.00001532415,0.000003538829],"category_scores_gemma":[0.00002124874,0.0000496704,0.00002499008,0.0001929618,0.00006227878,0.0005781011,0.0002257201,0.00009069332,0.000001369154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005822831,"about_ca_system_score_gemma":0.0000762676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003053871,"about_ca_topic_score_gemma":0.00001073516,"domain_scores_codex":[0.9989309,0.00002351259,0.0003790319,0.0001048052,0.0003683618,0.0001933593],"domain_scores_gemma":[0.999219,0.0001843459,0.0001826894,0.0001973381,0.0001442888,0.00007232084],"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":[0.0004053533,0.0002094124,0.1435136,0.0003462643,0.0005706788,0.00001747713,0.01023791,0.3154023,0.01324323,0.004758999,0.03390089,0.4773939],"study_design_scores_gemma":[0.0004007013,0.0001018816,0.004165751,0.0004817232,0.0000043919,0.000008349193,0.0002243373,0.9754733,0.0008053664,0.0003466097,0.01791092,0.00007664243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2120175,0.0003691023,0.7832198,0.002190048,0.00144892,0.0001956561,0.00009017805,0.00007202498,0.0003968267],"genre_scores_gemma":[0.9915015,0.0001654538,0.007954031,0.0002122959,0.0001128779,0.000001037206,0.00002558112,0.000007542116,0.00001966446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.779484,"threshold_uncertainty_score":0.20255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06634491092937526,"score_gpt":0.3195843439790234,"score_spread":0.2532394330496481,"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."}}