{"id":"W4403584346","doi":"10.1007/978-3-031-39650-2_7","title":"Edge Computing and Distributed Intelligence","year":2023,"lang":"en","type":"book-chapter","venue":"Springer handbooks","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quebec Network for Research on Aging; Université de Montréal; Hôtel-Dieu de Montréal","funders":"","keywords":"Computer science; Enhanced Data Rates for GSM Evolution; Distributed computing; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004200494,0.0004969959,0.0005094032,0.0002636628,0.0003537445,0.0004281373,0.001041643,0.000318947,0.000005753345],"category_scores_gemma":[0.00004051349,0.0005137197,0.0001575849,0.00008671314,0.0001508292,0.0001308554,0.002067358,0.0006817054,0.0004596027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007679448,"about_ca_system_score_gemma":0.00009521378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001166316,"about_ca_topic_score_gemma":0.000003575311,"domain_scores_codex":[0.9975698,0.00001923108,0.0005143129,0.0009438283,0.0003675562,0.0005852512],"domain_scores_gemma":[0.9983941,0.0002493067,0.0002584866,0.0007694829,0.0001221928,0.0002064873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001019754,0.00001872958,0.0001660976,0.0003168715,0.0002151541,0.0004222195,0.001657783,0.00005958325,0.0001000824,0.4034467,0.01155153,0.582035],"study_design_scores_gemma":[0.0006433312,0.0002881193,0.000863796,0.005165209,0.0001431115,0.0002085894,0.00002270109,0.08630566,0.002224613,0.2420176,0.6580668,0.00405048],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0001556421,0.001382643,0.7664894,0.0001946634,0.01399887,0.0003644482,0.000004558247,0.001409134,0.2160006],"genre_scores_gemma":[0.0203937,0.0008945068,0.04828501,0.0009412724,0.01844496,0.00001993404,0.0001283436,0.0006125213,0.9102798],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7182044,"threshold_uncertainty_score":0.9997314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03656514216986625,"score_gpt":0.2483515498200019,"score_spread":0.2117864076501357,"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."}}