{"id":"W4283013532","doi":"10.18137/cardiometry.2022.22.444455","title":"A distributed e-health management model with edge computing in healthcare framework","year":2022,"lang":"en","type":"article","venue":"Cardiometry","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Pareto principle; Depreciation (economics); Enhanced Data Rates for GSM Evolution; Negotiation; Health care; Resource allocation; Healthcare system; Wireless; Channel (broadcasting); Computer network; Artificial intelligence; Economics; Microeconomics; Operations management; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001043099,0.0001924653,0.0003777173,0.0006251965,0.0005746472,0.0001100397,0.0009789744,0.00004241276,7.585161e-7],"category_scores_gemma":[0.000014252,0.0001995099,0.00008792818,0.004212091,0.00002633209,0.0001277049,0.001523253,0.0006465975,0.000005304586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006543409,"about_ca_system_score_gemma":0.0001728226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005979296,"about_ca_topic_score_gemma":8.098976e-7,"domain_scores_codex":[0.9975044,0.0002118632,0.000341295,0.0006212209,0.0005893144,0.0007319188],"domain_scores_gemma":[0.9988438,0.000089578,0.0001396702,0.0007171727,0.00004425657,0.0001654785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006456719,0.0003599912,0.059299,0.0008261805,0.0002268639,0.0007604375,0.006006693,0.4330817,0.000003561323,0.07058033,0.02808622,0.4007044],"study_design_scores_gemma":[0.0007763085,0.0002266905,0.0255259,0.0001664373,0.000008661667,0.00008515976,0.0003129287,0.9588442,0.000005410993,0.005363007,0.00815557,0.0005297412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02809631,0.0008225344,0.9643291,0.002907989,0.002622767,0.0003116901,0.000004434114,0.0002593359,0.0006458805],"genre_scores_gemma":[0.9042695,0.000007564165,0.09382913,0.001494957,0.0003050888,0.00002195995,0.00002206862,0.00001933383,0.00003043679],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8761731,"threshold_uncertainty_score":0.8135778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850110724948055,"score_gpt":0.2728991911748929,"score_spread":0.2543980839254124,"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."}}