{"id":"W2941668132","doi":"","title":"Old Techniques in Differentially Private Linear Regression.","year":2019,"lang":"en","type":"article","venue":"Algorithmic Learning Theory","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Linear regression; Computer science; Statistics; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.002436142,0.0002185201,0.000338155,0.0002422372,0.0000792551,0.00003326262,0.0002866359,0.000186488,0.0003316358],"category_scores_gemma":[0.001191921,0.0001800363,0.00008652583,0.0002156297,0.00005049894,0.000127257,0.0001244281,0.0006318568,0.0001513799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007257069,"about_ca_system_score_gemma":0.00002852172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000269725,"about_ca_topic_score_gemma":0.000001485227,"domain_scores_codex":[0.9981282,0.0006010485,0.0003940262,0.0003313125,0.0002395519,0.0003058366],"domain_scores_gemma":[0.9980303,0.001231706,0.0002010994,0.0004247692,0.00006063658,0.00005146947],"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":[0.000428797,0.0007159709,0.05648107,0.0006581558,0.0001652213,0.00005910187,0.0055077,0.0001629772,0.01783032,0.4248807,0.001423381,0.4916866],"study_design_scores_gemma":[0.0009414415,0.0003097004,0.004749742,0.001432148,0.00003378985,0.0000290296,0.0003023038,0.01040231,0.04290889,0.9285349,0.009489298,0.0008664074],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8303974,0.0000650436,0.1615932,0.00009559798,0.0002284336,0.0005671515,0.000002561258,0.001863973,0.005186648],"genre_scores_gemma":[0.7538636,0.00008247158,0.232864,0.0001019155,0.0001572825,0.00007720281,0.0000260747,0.0001081511,0.01271924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5036542,"threshold_uncertainty_score":0.7341668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02917136203369002,"score_gpt":0.3203901574777243,"score_spread":0.2912187954440343,"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."}}