{"id":"W2801477319","doi":"10.1080/01621459.2018.1469991","title":"Capture-Recapture Methods for Data on the Activation of Applications on Mobile Phones","year":2018,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Census and Population Estimation","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Mark and recapture; Identification (biology); Context (archaeology); Automatic identification and data capture; Estimator; Mobile device; Data mining; Parametric statistics; Real-time computing; Variance (accounting); Mobile broadband; Statistics; Telecommunications; World Wide Web; Geography","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":[0.05581915,0.002577876,0.003366,0.004560657,0.001717526,0.002801609,0.008981871,0.005018733,0.004677551],"category_scores_gemma":[0.1076493,0.002020582,0.00554372,0.007107659,0.003221662,0.005015139,0.003613272,0.005495109,0.002353562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002626384,"about_ca_system_score_gemma":0.001793254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123247,"about_ca_topic_score_gemma":0.008881197,"domain_scores_codex":[0.9766732,0.01323886,0.001198935,0.006320192,0.002059113,0.0005096041],"domain_scores_gemma":[0.9083009,0.06143597,0.01036391,0.01610184,0.003367624,0.0004296205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005884194,0.0004781497,0.06072233,0.002978178,0.005398979,0.001204491,0.00221193,0.3786313,0.004293108,0.3144647,0.01195794,0.2170705],"study_design_scores_gemma":[0.0001717021,0.0008027141,0.02454277,0.0005351412,0.0009118816,0.0007977517,0.0006360961,0.7297986,0.003769255,0.2061448,0.03146608,0.0004232138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00600184,0.001014615,0.9894853,0.0002384606,0.000146099,0.0004578345,0.001563455,0.0004389459,0.0006534231],"genre_scores_gemma":[0.1501077,0.00197585,0.8247539,0.0008687222,0.0004387737,0.004881953,0.009661844,0.0002945194,0.007016751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05581915,"threshold_uncertainty_score":0.2952034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07360517283819713,"score_gpt":0.4430409186927909,"score_spread":0.3694357458545938,"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."}}