{"id":"W4399471733","doi":"10.23977/jeis.2024.090209","title":"Privacy Protection in Information and Communication Technology Applications Based on Big Data","year":2024,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Internet privacy; Computer security; Data science; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00454546,0.00007582557,0.0001200557,0.002330077,0.0002554208,0.0009508209,0.001362774,0.00008005952,0.000003064383],"category_scores_gemma":[0.001515335,0.00005480095,0.00001434087,0.003877431,0.0003127975,0.0107699,0.0003342112,0.0004015837,0.00001722901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001005385,"about_ca_system_score_gemma":0.0004966996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005551421,"about_ca_topic_score_gemma":0.000006641258,"domain_scores_codex":[0.9981892,0.00002140648,0.0008046779,0.000141699,0.0006816474,0.0001613953],"domain_scores_gemma":[0.998085,0.0001743258,0.0004431359,0.0007914288,0.0004582593,0.00004786992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007824641,0.00001171845,0.0001185608,0.000008107626,0.000001141499,5.909208e-8,0.00009083484,0.0001458083,0.0002110213,0.08523545,0.0002718849,0.9138976],"study_design_scores_gemma":[0.0002170305,0.0001614442,0.002322005,0.00005318582,0.000004723481,0.00004331359,0.0004910668,0.2311468,0.0004134698,0.03608031,0.7289811,0.00008553648],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1066374,0.002554432,0.8340516,0.05281201,0.0002294181,0.001212651,0.00008978238,0.0001231132,0.002289581],"genre_scores_gemma":[0.9951816,0.001527357,0.003020563,0.0002110733,0.00001372462,0.00002789323,0.00001330473,0.000001695845,0.000002744426],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.913812,"threshold_uncertainty_score":0.9168788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1411167137173094,"score_gpt":0.3710498922600756,"score_spread":0.2299331785427662,"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."}}