{"id":"W2470801513","doi":"10.1111/cgf.12905","title":"Using Visualization to Explore Original and Anonymized LBSN Data","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates - Technology Futures","keywords":"Computer science; Visualization; Data mining; Data science; Data visualization; Domain (mathematical analysis); Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005437083,0.001229332,0.0005573069,0.004548453,0.001109869,0.003872206,0.0009528583,0.0008045619,0.004296335],"category_scores_gemma":[0.01979759,0.0004001407,0.0006719198,0.00270848,0.00097465,0.003621906,0.004070998,0.001498073,0.0007494446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008948044,"about_ca_system_score_gemma":0.001128242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004113331,"about_ca_topic_score_gemma":0.004128436,"domain_scores_codex":[0.9974743,0.001315531,0.0001737286,0.0002269222,0.0006751909,0.000134386],"domain_scores_gemma":[0.984156,0.01001031,0.0009433171,0.002588301,0.001927816,0.0003742653],"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":[0.001914447,0.0005895796,0.02613814,0.002781877,0.0004208379,0.002908904,0.06167845,0.1249885,0.04249277,0.08458593,0.1294277,0.522073],"study_design_scores_gemma":[0.0002135404,0.0002689511,0.01102,0.0009602865,0.0001142698,0.0007417286,0.01036253,0.5678564,0.03673955,0.09488824,0.2765373,0.0002972787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.154269,0.000869684,0.7680145,0.004524492,0.0004783132,0.0006174091,0.009901635,0.04862664,0.01269833],"genre_scores_gemma":[0.4682246,0.0007339088,0.5154929,0.0004000557,0.000130392,0.0005074917,0.008652242,0.003451537,0.002406888],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005437083,"threshold_uncertainty_score":0.02875435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1656647477140332,"score_gpt":0.4002914702619073,"score_spread":0.2346267225478741,"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."}}