{"id":"W4240421454","doi":"10.1007/978-1-4899-7502-7_979-1","title":"Machine Learning with Privacy","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Machine learning; Interpretability; Differential privacy; Artificial intelligence; Information privacy; Raw data; Cryptography; Privacy software; Computer security; Data mining","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006895034,0.0008587435,0.0006568513,0.0008891663,0.0008783977,0.003627646,0.0007371767,0.001645934,0.01787718],"category_scores_gemma":[0.002420041,0.0004820509,0.0004424198,0.001637905,0.00259657,0.005363957,0.001503007,0.004066521,0.009885459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482589,"about_ca_system_score_gemma":0.0007513143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005609315,"about_ca_topic_score_gemma":0.0007347223,"domain_scores_codex":[0.9992338,0.0002283888,0.00002640685,0.0001465469,0.0003221606,0.00004252599],"domain_scores_gemma":[0.9992987,0.0004407617,0.00002950432,0.0001658037,0.00004793795,0.00001729119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000113195,0.00002154837,0.00006136925,0.000143835,0.000009397047,0.00002292412,0.0001056618,0.001125153,0.0002916218,0.8012684,0.0861873,0.1107515],"study_design_scores_gemma":[0.000002971788,0.00001002961,0.000107089,0.0001201243,0.000004581355,0.000108868,0.00002243882,0.003099123,0.0004939309,0.6590968,0.3369252,0.000008857141],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.001943313,0.06087017,0.2486781,0.01626616,0.002555107,0.00008806433,0.000647969,0.0008354562,0.6681156],"genre_scores_gemma":[0.09378919,0.05406702,0.09087582,0.009120268,0.005911134,0.0003278711,0.00144636,0.0008603766,0.743602],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01787718,"threshold_uncertainty_score":0.05980515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03095069278585965,"score_gpt":0.2440843534989755,"score_spread":0.2131336607131158,"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."}}