{"id":"W4385276677","doi":"10.32604/csse.2023.039736","title":"Evaluation of IoT Measurement Solutions from a Metrology Perspective","year":2023,"lang":"en","type":"article","venue":"Computer Systems Science and Engineering","topic":"Green IT and Sustainability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Metrology; Computer science; Internet of Things; Strengths and weaknesses; Reliability (semiconductor); Performance measurement; Data science; Identification (biology); Scalability; Measure (data warehouse); Standardization; Reliability engineering; Systems engineering; Risk analysis (engineering); Data mining; Computer security; Engineering; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1822851,0.001575368,0.002572716,0.03763766,0.002060582,0.00897882,0.002872969,0.00185598,0.001848794],"category_scores_gemma":[0.3470239,0.0008615247,0.00379298,0.03189774,0.003929115,0.01238678,0.007082153,0.001617569,0.0003215441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01096626,"about_ca_system_score_gemma":0.01880993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005005582,"about_ca_topic_score_gemma":0.004689557,"domain_scores_codex":[0.7312657,0.1627959,0.03323118,0.005451304,0.06428052,0.002975329],"domain_scores_gemma":[0.5984296,0.271117,0.03675301,0.01082183,0.08126317,0.001615346],"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":[0.0005884026,0.0003750937,0.0616175,0.05836582,0.003095856,0.0003827408,0.02781167,0.0153256,0.005003098,0.1133522,0.006455198,0.7076269],"study_design_scores_gemma":[0.0007393034,0.007651969,0.1716937,0.1608271,0.01398131,0.001921483,0.1423233,0.077779,0.0352424,0.1486688,0.2381799,0.0009918985],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4036976,0.1341595,0.3089901,0.02157212,0.001148615,0.009605291,0.003620594,0.0007569011,0.1164494],"genre_scores_gemma":[0.8122581,0.01550502,0.1625191,0.00111265,0.0001696743,0.006229583,0.001249299,0.00009704651,0.0008595275],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1822851,"threshold_uncertainty_score":0.9640274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05991634260505513,"score_gpt":0.2448246977673012,"score_spread":0.1849083551622461,"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."}}