{"id":"W2032630728","doi":"10.1007/s00224-011-9338-3","title":"Maintaining Privacy on a Line","year":2011,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Mitacs","keywords":"Variety (cybernetics); Task (project management); Computer science; Position (finance); Sequence (biology); Line (geometry); Internet privacy; Computer security; Artificial intelligence; Mathematics; Business; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.002685025,0.000192712,0.0003434094,0.0002335754,0.000111655,0.00005724101,0.02133298,0.0001046224,0.000007453654],"category_scores_gemma":[0.006470415,0.0001728221,0.00006709567,0.0003754419,0.0001438253,0.0002025847,0.02929473,0.0002625276,0.00005733283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000543229,"about_ca_system_score_gemma":0.00004140499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002876979,"about_ca_topic_score_gemma":1.50235e-7,"domain_scores_codex":[0.9979805,0.000350953,0.000500295,0.0004564762,0.0003214019,0.000390321],"domain_scores_gemma":[0.9919866,0.0006267349,0.0003874302,0.006853176,0.00008810211,0.00005800256],"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":[0.00002914927,0.0001039936,0.000296584,0.00007570926,0.00005317074,0.0000264952,0.001839949,0.0002617415,0.0002739951,0.9704302,0.003132054,0.02347696],"study_design_scores_gemma":[0.0004392791,0.0005736265,0.0007750663,0.000811947,0.000009616679,0.00006770088,0.0003192097,0.3376102,0.007476397,0.6511022,0.0004351173,0.0003796729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1021345,0.0001433031,0.8811264,0.0003942356,0.0009056021,0.0002318196,0.000003029344,0.001247673,0.01381343],"genre_scores_gemma":[0.8852811,0.000002695194,0.1145194,0.00005940167,0.00008001071,0.00000339021,0.000001204867,0.00001569808,0.00003709397],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7831466,"threshold_uncertainty_score":0.9839621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07770176045766537,"score_gpt":0.2857083316337838,"score_spread":0.2080065711761184,"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."}}