{"id":"W4388442663","doi":"10.1007/978-3-031-47448-4_9","title":"Meta-heuristic Algorithms in IoT-Based Application: A Systematic Review","year":2023,"lang":"en","type":"review","venue":"Lecture notes in networks and systems","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Heuristic; Meta heuristic; Internet of Things; Artificial intelligence; Data science; Big data; Automation; The Internet; Analytics; Reading (process); Machine learning; Data mining; Algorithm; World Wide Web; Engineering","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":[0.003095827,0.0007082567,0.005492818,0.000405094,0.0001044166,0.0003295418,0.001201299,0.0004914048,4.475365e-7],"category_scores_gemma":[0.0002845218,0.0004828842,0.0005206657,0.002662849,0.00003419567,0.00005403025,0.0002504266,0.0008476373,0.00002653514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609515,"about_ca_system_score_gemma":0.0001535536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001147778,"about_ca_topic_score_gemma":0.0000191397,"domain_scores_codex":[0.9946916,0.001186491,0.002081604,0.001023055,0.0003921384,0.0006250896],"domain_scores_gemma":[0.9948035,0.002897347,0.0008939829,0.001222771,0.00006910729,0.0001132157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[2.833671e-7,0.00001591204,0.000001608084,0.8950063,0.0002794868,0.00006591954,0.00003218852,0.006010864,2.102064e-9,0.0001074181,0.0001605787,0.09831943],"study_design_scores_gemma":[0.0000769489,0.00001666933,2.528183e-7,0.4499152,0.00148052,0.00007196738,3.183325e-7,0.5223684,4.653969e-9,0.00008951082,0.02556429,0.0004159063],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[1.205335e-8,0.5641469,0.4312702,0.00003370683,0.002056383,0.002379083,6.685518e-7,0.0001011653,0.00001179235],"genre_scores_gemma":[0.00002812874,0.9955656,0.000829011,0.0002025338,0.001425915,0.001835736,0.00003238927,0.00006315476,0.00001756489],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5163576,"threshold_uncertainty_score":0.9997623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0854925086116694,"score_gpt":0.3230005658303169,"score_spread":0.2375080572186475,"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."}}