{"id":"W4387969948","doi":"10.1109/mcom.2023.10298086","title":"Global Communications Newsletter","year":2023,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Telecommunications; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006617053,0.001270238,0.0005777568,0.001976237,0.001271961,0.006569255,0.0009519617,0.003200134,0.487018],"category_scores_gemma":[0.002526525,0.0003350197,0.0004757926,0.00280243,0.0004196773,0.002823665,0.001608232,0.002855027,0.4822437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196635,"about_ca_system_score_gemma":0.002103041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004212043,"about_ca_topic_score_gemma":0.007405916,"domain_scores_codex":[0.9993308,0.00006059293,0.00003136638,0.0001158992,0.0003496312,0.0001117429],"domain_scores_gemma":[0.9984949,0.000199052,0.00008862419,0.0001437651,0.0006905071,0.000383169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001200498,0.00001174717,0.00005632425,0.00005417312,0.000001349899,0.00002930595,0.00001324335,0.00001260504,0.0001013295,0.001098764,0.9694417,0.02916747],"study_design_scores_gemma":[0.000002797173,0.000006920629,0.0002431015,0.00003664631,9.510625e-7,0.00001852772,0.00002374865,0.00001453639,0.00002924559,0.0001436497,0.999478,0.000001952195],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005349933,0.005818245,0.0004480525,0.01764546,0.02583846,0.00009791691,0.005071776,0.001277263,0.9432677],"genre_scores_gemma":[0.002133149,0.003031988,0.0002268344,0.005375696,0.004663664,0.0000509882,0.003530751,0.0002758071,0.9807112],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.487018,"threshold_uncertainty_score":0.7317066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08188808701700448,"score_gpt":0.315273080390297,"score_spread":0.2333849933732925,"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."}}