{"id":"W4319769514","doi":"10.1016/j.eng.2022.12.008","title":"Data-Driven Learning for Data Rights, Data Pricing, and Privacy Computing","year":2023,"lang":"en","type":"article","venue":"Engineering","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Big data; Computer science; Information privacy; Transaction data; Data Protection Act 1998; Data science; Database transaction; Transaction cost; Key (lock); Computer security; Business; Data mining; Database; Finance","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":["metaresearch","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001290724,0.0002073154,0.0002348412,0.0002263076,0.0002493674,0.0003461252,0.06928876,0.0000879127,0.000001422881],"category_scores_gemma":[0.01984508,0.0002100045,0.00001148739,0.0006947329,0.00003507845,0.002375494,0.4046637,0.0003919904,0.00002032429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002805813,"about_ca_system_score_gemma":0.00003314258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003007859,"about_ca_topic_score_gemma":0.000004802156,"domain_scores_codex":[0.9975413,0.00002343831,0.0002912111,0.001347522,0.0002490129,0.0005475277],"domain_scores_gemma":[0.9742952,0.0006804,0.00009884498,0.02482396,0.00002651671,0.00007508573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005999539,0.000049645,0.002476403,0.0006449871,0.0002781711,0.0001236113,0.0004207294,0.03409886,0.001998141,0.006275846,0.7957251,0.1579025],"study_design_scores_gemma":[0.0001778829,0.0000142479,0.0004972825,0.00008199387,0.000009663714,0.00001320202,0.000007670777,0.8695424,0.00007738399,0.001049103,0.1283061,0.0002230521],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00728288,0.0002543205,0.9853824,0.00252943,0.0004745327,0.000258655,0.0002720749,0.003518727,0.00002693543],"genre_scores_gemma":[0.1063332,0.00007481287,0.8898062,0.00001999883,0.0001799414,0.000005336437,0.003516147,0.00003731344,0.00002705305],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8354436,"threshold_uncertainty_score":0.9884112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08175695664528417,"score_gpt":0.3090243235255185,"score_spread":0.2272673668802344,"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."}}