{"id":"W2797934678","doi":"","title":"On keeping secrets","year":2015,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Computer science; Intelligent agent; Secrecy; Software agent; Private information retrieval; Computer security; Obligation; Order (exchange); Internet privacy; Artificial intelligence; Business","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002323056,0.0001284802,0.0001432137,0.0001405406,0.0005974698,0.0003746174,0.0003735711,0.0002004396,0.0005536728],"category_scores_gemma":[0.009831256,0.0001334236,0.00006160812,0.0003410851,0.0004056352,0.0003114134,0.00002917347,0.0004077284,0.001313658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003411847,"about_ca_system_score_gemma":0.001601666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007532888,"about_ca_topic_score_gemma":0.001634893,"domain_scores_codex":[0.9972026,0.0002441514,0.0002737957,0.0002810017,0.001657146,0.0003413313],"domain_scores_gemma":[0.9967657,0.0006662715,0.000108146,0.0001151339,0.002005684,0.0003390457],"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":[0.00004239513,0.0000783056,0.000008035352,0.000001056117,0.000005845109,0.000002740713,0.00608443,0.0003304484,0.00004387548,0.977009,0.001085175,0.01530872],"study_design_scores_gemma":[0.0000233269,0.0001468243,0.00004458493,0.00003776314,0.000002421433,1.973967e-7,0.004533637,0.001707234,0.0009257048,0.9867489,0.005651924,0.0001774813],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01963157,0.00001443682,0.004037492,0.0351462,0.001027228,0.000243577,0.00001617776,0.0001287449,0.9397546],"genre_scores_gemma":[0.9939849,0.00003097189,0.0002010683,0.004230857,0.0005640565,0.00001043349,0.000007304751,0.000009761898,0.0009605805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9743534,"threshold_uncertainty_score":0.9994639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4651903065479184,"score_gpt":0.4825425060457487,"score_spread":0.01735219949783035,"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."}}