{"id":"W2999940786","doi":"10.29012/jpc.697","title":"Program for TPDP 2018","year":2018,"lang":"en","type":"article","venue":"Journal of Privacy and Confidentiality","topic":"Legal and Policy Issues","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Differential privacy; Differential (mechanical device); Computer science; Library science; Data science; Engineering; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01128479,0.0006447948,0.0006662459,0.001649741,0.00357986,0.006087788,0.002872864,0.0031096,0.5260924],"category_scores_gemma":[0.02783037,0.000457103,0.000945801,0.001452201,0.0008468046,0.00349288,0.007024626,0.004667836,0.2523213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006029786,"about_ca_system_score_gemma":0.01350101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009232223,"about_ca_topic_score_gemma":0.01217113,"domain_scores_codex":[0.9914331,0.001781736,0.0002536077,0.0009986282,0.003988367,0.001544493],"domain_scores_gemma":[0.9795018,0.002318951,0.0003981908,0.002092805,0.008959373,0.006729016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000484001,0.00005766998,0.00006844497,0.00004312268,0.000002132065,0.00001988042,0.00006210324,0.00008834685,0.0001008931,0.01731702,0.9628753,0.01931675],"study_design_scores_gemma":[0.00003322302,0.0000309638,0.000206062,0.0000356487,0.000001427551,0.00001704233,0.00005591222,0.000294495,0.0001037867,0.004609417,0.994606,0.000005928206],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002252691,0.001006258,0.04387947,0.107684,0.03282764,0.003236827,0.01915272,0.01462767,0.7753327],"genre_scores_gemma":[0.01831621,0.0006361742,0.01896132,0.01171361,0.006102426,0.003377301,0.01266492,0.003903149,0.9243249],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4739076,"threshold_uncertainty_score":0.6759716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05281254402730334,"score_gpt":0.4200759570956735,"score_spread":0.3672634130683702,"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."}}