{"id":"W4285813993","doi":"10.1109/iwcmc55113.2022.9824981","title":"Publishing Private High-dimensional Datasets: A Topological Approach","year":2022,"lang":"en","type":"article","venue":"2022 International Wireless Communications and Mobile Computing (IWCMC)","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Dependency (UML); Publication; Graph; Publishing; Dependency graph; Data mining; Data publishing; Theoretical computer science; Key (lock); Data science; Information retrieval; Artificial intelligence","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":["sts","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.001112248,0.000187875,0.0002711018,0.00038797,0.001379379,0.0006787726,0.005496634,0.00005945022,0.0002450579],"category_scores_gemma":[0.0001316464,0.0001720428,0.0001011685,0.00118743,0.0002102402,0.0005569219,0.01463681,0.0007239699,0.00001119923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000124436,"about_ca_system_score_gemma":0.00004961513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003146215,"about_ca_topic_score_gemma":0.000006006846,"domain_scores_codex":[0.997494,0.0003977418,0.0004877136,0.0006468469,0.000671095,0.0003025537],"domain_scores_gemma":[0.9972999,0.0005670968,0.0002706847,0.001609485,0.0001211121,0.0001317139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001589403,0.001199785,0.001982566,0.000008337439,0.0002189219,0.00001912525,0.000369576,0.009835511,0.000174907,0.8149719,0.009707038,0.1614965],"study_design_scores_gemma":[0.0005947212,0.0001604651,0.003016773,0.000008410069,0.00002279167,0.0001523906,0.0003264713,0.8214781,0.00001432312,0.005488504,0.1683543,0.00038277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6474838,0.003278403,0.3209078,0.02033077,0.001392052,0.0007672664,0.001493069,0.0006956719,0.003651146],"genre_scores_gemma":[0.968028,0.0001485201,0.02720718,0.001155333,0.00005990159,0.0001432503,0.003119946,0.000007123839,0.0001307332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8116426,"threshold_uncertainty_score":0.9999207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02408600087161051,"score_gpt":0.2711633523553911,"score_spread":0.2470773514837806,"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."}}