{"id":"W7130411760","doi":"10.32628/ijsrst22548681","title":"Cyber-Physical Workforce Analytics: Linking IoT Devices, Artificial Intelligence, and Enterprise ERP Systems for Autonomous Healthcare and Talent Operations","year":2022,"lang":"","type":"article","venue":"International Journal of Scientific Research in Science and Technology","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Workforce planning; Workforce; Analytics; Cloud computing; Workforce management; Operationalization; Service (business); Workflow; Staffing","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":[0.001262635,0.0004719941,0.0002103341,0.001121142,0.0004402062,0.003421595,0.0006618412,0.0006322896,0.002179797],"category_scores_gemma":[0.002106291,0.0002459189,0.000355444,0.001044799,0.001040759,0.00441156,0.0024001,0.0008610081,0.0004813454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008238127,"about_ca_system_score_gemma":0.001876703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001918673,"about_ca_topic_score_gemma":0.002560277,"domain_scores_codex":[0.9994073,0.0001966455,0.00003764189,0.0001021542,0.0001887678,0.00006758039],"domain_scores_gemma":[0.9990904,0.0003824488,0.0001547879,0.0001373943,0.000148818,0.00008596809],"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":[0.0001388663,0.0003201318,0.02445886,0.0006495092,0.0001528313,0.0004525769,0.002585059,0.04450486,0.01031517,0.3283258,0.02099036,0.5671059],"study_design_scores_gemma":[0.00002792164,0.0002285832,0.01957948,0.000784349,0.0001059539,0.0004570447,0.004778479,0.4011705,0.007943534,0.4229187,0.1418894,0.0001160665],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.09677333,0.003941655,0.8054953,0.01755594,0.0006312894,0.0003179139,0.0005647062,0.001881788,0.07283808],"genre_scores_gemma":[0.8473039,0.003187165,0.1421755,0.001497393,0.0003228806,0.0001141895,0.0003271147,0.0000862012,0.004985535],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.003421595,"threshold_uncertainty_score":0.007292151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1177175361182044,"score_gpt":0.3989722806730254,"score_spread":0.281254744554821,"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."}}