{"id":"W1516571311","doi":"10.11575/prism/30651","title":"BALANCING PRIVACY AND AWARENESS FOR TELECOMMUTERS USING BLUR FILTRATION","year":2003,"lang":"en","type":"article","venue":"PRISM (University of Calgary)","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Filtration (mathematics); Telecommuting; Privacy laws of the United States; Privacy protection; Computer science; Internet privacy; Motion blur; Work (physics); Information privacy; Computer security; Computer vision; Image (mathematics); Engineering","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":[0.00007122695,0.000056545,0.00008744426,0.00005545258,0.00008938992,0.000008096975,0.00005584209,0.00004813955,0.00001346036],"category_scores_gemma":[0.00001378253,0.00007774385,0.00002782416,0.00005541768,0.00002046078,0.0001476126,0.00001095614,0.00004451782,7.064108e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003627576,"about_ca_system_score_gemma":0.00002067476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003257089,"about_ca_topic_score_gemma":0.000007957338,"domain_scores_codex":[0.9997202,0.00001210185,0.00005677648,0.00007154331,0.00005104451,0.00008828841],"domain_scores_gemma":[0.9998049,0.00002961042,0.00002450417,0.00008066477,0.00002488553,0.0000354765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000232067,0.0003405156,0.1014112,0.003216668,0.0008571589,0.00004566185,0.03196033,0.0239698,0.2133208,0.07427659,0.00594911,0.5444201],"study_design_scores_gemma":[0.0004801853,0.0000137319,0.004225128,0.00001735967,0.00002572226,0.000003096344,0.000115883,0.9904617,0.001177686,0.0003622458,0.003006269,0.0001110129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4149731,0.00003584391,0.5841151,0.00001468267,0.00003964418,0.00006583309,2.737007e-7,0.00003151908,0.0007239573],"genre_scores_gemma":[0.8331731,0.00004594846,0.166627,0.00001445071,0.000003801951,2.184947e-7,0.00001025703,0.00001091765,0.0001143437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9664919,"threshold_uncertainty_score":0.3170303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01279505913729446,"score_gpt":0.2053712940765567,"score_spread":0.1925762349392623,"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."}}