{"id":"W2819871557","doi":"10.1145/3214265","title":"Uniqueness in the City","year":2018,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Point of interest; Identification (biology); Uniqueness; Computer science; Geography; Internet privacy; World Wide Web; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001250314,0.0002150218,0.0005726009,0.001696935,0.002098226,0.004825605,0.0007210153,0.0007744849,0.007169333],"category_scores_gemma":[0.009837414,0.0002653069,0.0006705857,0.004903588,0.002393472,0.003869461,0.00343798,0.0009191521,0.0009844247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439076,"about_ca_system_score_gemma":0.0010871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01124992,"about_ca_topic_score_gemma":0.01179947,"domain_scores_codex":[0.9981803,0.0005469698,0.0000888674,0.0006653566,0.0002984184,0.0002201117],"domain_scores_gemma":[0.9944034,0.002056513,0.001217113,0.001517601,0.0004928921,0.000312566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003652772,0.00007726892,0.571008,0.0003804583,0.000301831,0.0005768634,0.007316422,0.02195046,0.001015442,0.3016456,0.0130792,0.08228319],"study_design_scores_gemma":[0.00007574211,0.0001922271,0.4547175,0.0003488573,0.0003873389,0.003385726,0.02627932,0.07543941,0.003675257,0.2259999,0.2092636,0.0002351017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9097322,0.001631875,0.03450828,0.002542935,0.0001072761,0.00009140532,0.008121211,0.0001455335,0.04311929],"genre_scores_gemma":[0.9924505,0.0002692601,0.003699228,0.0001119537,0.000029366,0.00003468466,0.001339513,0.00002756508,0.002037994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01124992,"threshold_uncertainty_score":0.02398384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02171314456728697,"score_gpt":0.3172395846738736,"score_spread":0.2955264401065866,"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."}}