{"id":"W4312633198","doi":"10.1007/978-3-031-14264-2_1","title":"Data Sovereignty","year":2022,"lang":"en","type":"book-chapter","venue":"Progress in IS","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Sovereignty; Context (archaeology); Westphalian sovereignty; Corporate governance; Political science; Computer science; Law; Politics; Geography; Economics; Management","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","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.0005932289,0.0003641701,0.0003949308,0.0003392971,0.0001091654,0.0002086493,0.1241249,0.0003432744,0.001878311],"category_scores_gemma":[0.001546969,0.0003885819,0.00006099296,0.0001667491,0.0002530499,0.0009022137,0.5044455,0.001253469,0.0001640034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002003036,"about_ca_system_score_gemma":0.0001520909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008873693,"about_ca_topic_score_gemma":0.000007259922,"domain_scores_codex":[0.9967397,0.00002876596,0.0004225196,0.001583357,0.000779504,0.0004461574],"domain_scores_gemma":[0.9649748,0.0001218157,0.0002837283,0.03453358,0.00003444602,0.00005163279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002927461,0.00002454746,0.0002045406,0.0000420134,0.00003310653,0.0002075384,0.00001771152,1.044246e-7,4.744153e-8,0.3760571,0.416094,0.2073163],"study_design_scores_gemma":[0.00008952784,0.00002235148,0.00001227079,0.00006534042,0.000005329665,0.00001300821,0.000001131542,0.005719495,0.000006940555,0.5150329,0.4787658,0.0002658963],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.000004185531,0.02094582,0.00403054,0.03447375,0.001797973,0.0009039817,0.003484981,0.002351654,0.9320071],"genre_scores_gemma":[0.002212964,0.005257787,0.925824,0.001786025,0.0003755088,0.0003195607,0.002321413,0.0002783096,0.06162439],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9217935,"threshold_uncertainty_score":0.9998566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08858069520645197,"score_gpt":0.3145997028682344,"score_spread":0.2260190076617824,"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."}}