{"id":"W4400488219","doi":"10.1109/access.2024.3426279","title":"A Survey of Industrial AIoT: Opportunities, Challenges, and Directions","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pace; Computer science; Internet of Things; Industrial Internet; Variety (cybernetics); Key (lock); Industrial production; Manufacturing engineering; Data science; Artificial intelligence; Engineering management; Engineering; Computer security","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005618957,0.00008827781,0.0001335792,0.0001567511,0.00006942899,0.0002660847,0.0005047134,0.00006912168,0.00000181544],"category_scores_gemma":[0.0000648652,0.00008214256,0.00002543741,0.0003183264,0.0000402989,0.0005821162,0.0002360024,0.0001468815,0.000003505178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001622935,"about_ca_system_score_gemma":0.0001499006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006758594,"about_ca_topic_score_gemma":0.00006710205,"domain_scores_codex":[0.9991749,0.00009440389,0.0001784195,0.0002488088,0.0001383629,0.0001651306],"domain_scores_gemma":[0.9992873,0.000287831,0.00003951583,0.0002263093,0.00009314762,0.00006586801],"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":[0.000001866234,0.00002182825,0.0008704849,0.00003950682,0.00002880056,0.00002145127,0.0008056533,0.000002368952,0.00001670866,0.0009538845,0.01759106,0.9796464],"study_design_scores_gemma":[0.001554121,0.00047318,0.1845381,0.001437654,0.00008150955,0.0001548242,0.0001163163,0.1257123,0.005005711,0.008433751,0.6707646,0.001727892],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6116538,0.07277275,0.0764462,0.004683338,0.1983287,0.0006946423,0.00001838669,0.00161116,0.03379103],"genre_scores_gemma":[0.9960666,0.001502075,0.0001347735,0.00005031182,0.001990797,0.00000612298,0.000003425283,0.00001177736,0.0002341366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9779185,"threshold_uncertainty_score":0.3349676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3806522843531447,"score_gpt":0.3479959538909535,"score_spread":0.03265633046219124,"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."}}