{"id":"W2963634943","doi":"10.3390/info7010015","title":"Information Extraction Under Privacy Constraints","year":2016,"lang":"en","type":"article","venue":"MDPI (MDPI AG)","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Mutual information; Random variable; Joint probability distribution; Information theory; Mathematics; Quantization (signal processing); Gaussian; Constraint (computer-aided design); Computer science; Probability density function; Function (biology); Statistics","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":["open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.0003931613,0.0001734144,0.0001426243,0.0002136148,0.0001355111,0.0002326215,0.01161297,0.0001722022,0.0001625344],"category_scores_gemma":[0.006703374,0.0001277219,0.00005214119,0.0003333517,0.0002147712,0.004878141,0.0182092,0.000185352,0.001190126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001850096,"about_ca_system_score_gemma":0.0000940155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001604808,"about_ca_topic_score_gemma":0.000003035465,"domain_scores_codex":[0.9985346,0.00004971083,0.0003446961,0.000289665,0.0003851811,0.0003962054],"domain_scores_gemma":[0.9942084,0.0002124033,0.0002002296,0.005192855,0.0001076066,0.00007851333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007978393,0.00005255088,0.0006447782,0.00001861255,0.00002824299,0.000009192562,0.0001553836,0.000003843066,0.00515248,0.04536831,0.2007805,0.7477782],"study_design_scores_gemma":[0.001620475,0.0001418027,0.01764354,0.0001974269,0.00001428519,0.0001864097,0.0001368629,0.008564643,0.03414597,0.7609634,0.1755496,0.0008354994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02453839,0.00002665742,0.9264371,0.04089788,0.0008107946,0.0002130961,0.00002328558,0.001453124,0.005599676],"genre_scores_gemma":[0.889205,0.000052176,0.1099224,0.000568178,0.00005652218,0.00002652264,0.00001231142,0.000009507731,0.0001473747],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8646666,"threshold_uncertainty_score":0.9995875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02985263793982186,"score_gpt":0.2794588425650404,"score_spread":0.2496062046252186,"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."}}