{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006491884,0.00008246459,0.0001268722,0.0001732014,0.0005484685,0.0001128546,0.0003471043,0.00005859018,0.00006541771],"category_scores_gemma":[0.0000692684,0.00006571718,0.00003435415,0.0004997,0.0001906275,0.0003429666,0.0001624555,0.00003671828,0.0000133648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003378999,"about_ca_system_score_gemma":0.0001068709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009057643,"about_ca_topic_score_gemma":0.003232384,"domain_scores_codex":[0.9988774,0.000155634,0.000162675,0.000333097,0.0002401802,0.0002310282],"domain_scores_gemma":[0.999179,0.0001299859,0.00005184286,0.0003819776,0.0001176443,0.000139536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000714706,0.0002184198,0.1525827,0.00004285543,0.000162954,0.000006800234,0.01205549,0.00009675929,0.0003896722,0.6959944,0.01143603,0.1269425],"study_design_scores_gemma":[0.002350525,0.0002506808,0.009995069,0.0004084472,0.0002466216,0.000003219463,0.003244133,0.2255035,0.0001783632,0.05544492,0.7011234,0.001251136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1590161,0.00004058733,0.8379009,0.002542557,0.0001800683,0.0001547223,0.00001245025,0.00006370186,0.00008888912],"genre_scores_gemma":[0.9957255,0.00006931392,0.003041893,0.0007691183,0.0002816882,0.000004659767,0.00003216952,0.000008630559,0.00006703701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8367093,"threshold_uncertainty_score":0.4218432,"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."}}