{"id":"W3007414102","doi":"10.48550/arxiv.2002.11613","title":"The Differentially Private Lottery Ticket Mechanism","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Ticket; Mechanism (biology); Lottery; Business; Computer security; Internet privacy; Computer science; Economics; Microeconomics; Physics","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":[0.006382019,0.0007748588,0.001492276,0.0006982643,0.000807429,0.001615806,0.004475449,0.002414023,0.009929393],"category_scores_gemma":[0.02013991,0.000567223,0.0007945055,0.0008055504,0.002048273,0.00431639,0.0030778,0.004154569,0.002108192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095904,"about_ca_system_score_gemma":0.002382771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006052144,"about_ca_topic_score_gemma":0.0006846612,"domain_scores_codex":[0.9967964,0.001852947,0.00009729945,0.0005112886,0.0004471576,0.0002948608],"domain_scores_gemma":[0.9919795,0.004222184,0.0006555814,0.002162003,0.0004388106,0.000541941],"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":[0.003263092,0.001272193,0.00557267,0.0003732413,0.00023623,0.0002512771,0.0003669813,0.2526571,0.007867776,0.3491226,0.02492836,0.3540885],"study_design_scores_gemma":[0.0004284174,0.0004326803,0.000719222,0.0000419997,0.00003730455,0.0001859645,0.00003287848,0.7228443,0.002782114,0.2684906,0.003946614,0.00005798326],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05245142,0.0003649774,0.9357459,0.002587177,0.0002216982,0.0003451925,0.0006707753,0.001544729,0.006068249],"genre_scores_gemma":[0.83765,0.0002893564,0.1517021,0.0009712494,0.0001747991,0.0008007579,0.0005672253,0.0001645514,0.007679958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009929393,"threshold_uncertainty_score":0.03375173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2116538232630673,"score_gpt":0.2623952948573583,"score_spread":0.05074147159429096,"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."}}