{"id":"W4388543182","doi":"10.1007/978-3-031-46402-7","title":"Data Enclaves","year":2023,"lang":"es","type":"book","venue":"","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Social Sciences and Humanities Research Council of Canada; Copenhagen Business School","keywords":"Big data; Business; Internet privacy; Computer science; Data science; Data mining","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","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.001788516,0.0003727005,0.0005589405,0.0004681495,0.0003925514,0.0009367715,0.01645547,0.0007457342,0.003374543],"category_scores_gemma":[0.002925701,0.0002601806,0.0001163189,0.001178394,0.0006823234,0.0004972272,0.01347621,0.0006014507,0.07936583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004320086,"about_ca_system_score_gemma":0.0004908399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006716653,"about_ca_topic_score_gemma":0.0002293522,"domain_scores_codex":[0.9950804,0.00004113191,0.000953875,0.002015764,0.001452481,0.0004563465],"domain_scores_gemma":[0.985266,0.002334143,0.0004141304,0.01168164,0.0001808656,0.0001231658],"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":[7.95146e-7,0.00001379451,0.00001957068,0.000006217241,0.00001967614,0.000004986859,0.000003106241,2.895312e-7,0.00001145213,0.1606371,0.668854,0.1704291],"study_design_scores_gemma":[0.00005030909,0.00001859474,0.0002047478,0.00004829295,0.0000306611,0.000003573592,0.000308108,0.0005734836,0.00001969539,0.1528555,0.845599,0.0002880292],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002791253,0.0005981002,0.01263529,0.02190368,0.001283685,0.0008010755,0.04037806,0.001900467,0.9204717],"genre_scores_gemma":[0.0002232834,0.005004992,0.004463051,0.0003387032,0.0003274566,0.00003484984,0.004765716,0.00004791712,0.984794],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.176745,"threshold_uncertainty_score":0.999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6079265092522445,"score_gpt":0.4614987018091529,"score_spread":0.1464278074430915,"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."}}