{"id":"W4312007055","doi":"10.1109/tencon55691.2022.9977897","title":"IEEE Hong Kong Section 50th Anniversary 1972-2022: Advance Technology for Huminity – The Tech-Biz Intelligence","year":2022,"lang":"en","type":"article","venue":"TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON)","topic":"Age of Information Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University at Buffalo; University of California, San Diego; University of Illinois at Urbana-Champaign; SaskPower; University of Texas at Dallas; Chinese University of Hong Kong; Hong Kong Polytechnic University; University of Hong Kong; University of Toronto; University of Edinburgh; China Computer Federation; Hang Seng Management College; University of Alberta; University of Saskatchewan; Princeton University; State University of New York; University of Maryland, Baltimore County","keywords":"Section (typography); Friendship; China; Work (physics); Telecommunications; Engineering; Library science; Computer science; Sociology; Political science; Business; Advertising; Social science; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001368493,0.0005880073,0.0005688474,0.0009998642,0.002233288,0.0003109219,0.003702384,0.0002863497,0.0008361984],"category_scores_gemma":[0.0003272767,0.0005599391,0.000276145,0.003326943,0.0005495707,0.002711832,0.0009424664,0.001348121,0.0001119007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007042974,"about_ca_system_score_gemma":0.000813334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007187438,"about_ca_topic_score_gemma":0.00006250232,"domain_scores_codex":[0.9953285,0.000368403,0.001032307,0.001260791,0.001085394,0.0009245415],"domain_scores_gemma":[0.9956086,0.0004411855,0.001118425,0.001821774,0.0008192779,0.0001907624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008071329,0.001032516,0.0017426,0.000473067,0.0004592241,0.0003786648,0.01561209,0.145947,0.01638188,0.1868856,0.1301758,0.5001045],"study_design_scores_gemma":[0.001636167,0.002059996,0.0002580691,0.000153384,0.0001056265,0.0008971011,0.02165714,0.828921,0.01986787,0.02428509,0.09795801,0.002200576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008400062,0.0003370609,0.973852,0.006591085,0.004184853,0.001966579,0.00006069869,0.001059706,0.003547916],"genre_scores_gemma":[0.9641821,0.0009566419,0.01803975,0.001779834,0.0004851613,0.002104061,0.0001463048,0.00009932707,0.01220678],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9558123,"threshold_uncertainty_score":0.9996852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02844687340513785,"score_gpt":0.2528148511309296,"score_spread":0.2243679777257917,"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."}}