{"id":"W4378470119","doi":"10.2196/44286","title":"Convergence in Mobility Data Sets From Apple, Google, and Meta","year":2023,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Izaak Walton Killam Health Centre; Dalhousie University","funders":"","keywords":"Pandemic; Public health; Business; Download; Robustness (evolution); Convergence (economics); Meta-analysis; Geography; Coronavirus disease 2019 (COVID-19); Internet privacy; Infectious disease (medical specialty); Medicine; Computer science; Disease; World Wide Web; Economics; Economic growth; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002524595,0.0002579197,0.0009498913,0.0001744678,0.0001096309,0.00006418534,0.0003292723,0.0001035829,0.0001817753],"category_scores_gemma":[0.0009058581,0.0002250085,0.00004274257,0.0009287214,0.0001973261,0.0003328563,0.0005255,0.000282171,0.00006523079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006146293,"about_ca_system_score_gemma":0.0007276589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314771,"about_ca_topic_score_gemma":0.002245212,"domain_scores_codex":[0.9967472,0.0004109469,0.0006023946,0.00107554,0.0003924104,0.0007714863],"domain_scores_gemma":[0.9966984,0.0004277865,0.0001512731,0.001505329,0.00008578735,0.001131374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001059329,0.0001450511,0.9407608,0.0005011418,0.0001415542,0.00005145569,0.0002630696,5.884955e-7,0.000008856156,0.00006842748,0.0380891,0.01986403],"study_design_scores_gemma":[0.001064591,0.00006334791,0.8216575,0.000009155512,0.00000592961,0.000009688104,0.0001498462,0.003182695,2.952818e-7,0.0001040631,0.1735732,0.0001797683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9545935,0.007406313,0.00006059697,0.02588513,0.0002000419,0.001663547,0.009351733,0.0004305976,0.0004085434],"genre_scores_gemma":[0.9832734,0.003786022,0.0003248307,0.003646926,0.00007439883,0.0001914678,0.008479938,0.00003148917,0.000191565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1354841,"threshold_uncertainty_score":0.9175579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1096488974195229,"score_gpt":0.3718945443967333,"score_spread":0.2622456469772104,"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."}}