{"id":"W3104363285","doi":"10.1155/2020/8835981","title":"Mobile Phone Data in Urban Commuting: A Network Community Detection-Based Framework to Unveil the Spatial Structure of Commuting Demand","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mobile phone; Transport engineering; Urbanization; Sustainability; Computer science; Street network; Urban planning; Phone; Business; Geography; Civil engineering; Economic growth; Engineering; Telecommunications; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00158317,0.0001093719,0.0003136687,0.00007386006,0.0006485128,0.00003105347,0.0007423259,0.00009439036,0.00005968688],"category_scores_gemma":[0.0006802093,0.00009373351,0.00009370234,0.000981201,0.0001597773,0.0002350332,0.00001156532,0.0008573099,5.847478e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007060538,"about_ca_system_score_gemma":0.0002209689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004128032,"about_ca_topic_score_gemma":0.1018929,"domain_scores_codex":[0.9976836,0.0008144716,0.0007513242,0.0001211713,0.0004425172,0.0001869043],"domain_scores_gemma":[0.997565,0.0010303,0.0006300333,0.0003755385,0.0002784899,0.0001206851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002853658,0.0001015269,0.0392407,0.00005117447,0.0000412834,0.000001955708,0.09310416,0.8553784,0.001542214,0.0000738431,0.0000239861,0.01015535],"study_design_scores_gemma":[0.004845211,0.001990254,0.73026,0.001525025,0.0007917242,0.000001330046,0.2014522,0.0338172,0.007532492,0.008644507,0.008196698,0.0009433408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8794952,0.0001485803,0.1190707,0.000845662,0.000119333,0.0002583679,0.00003778828,0.00001203771,0.00001231975],"genre_scores_gemma":[0.9961576,0.00002304771,0.002964086,0.0005081327,0.0002769115,0.00000318743,0.00005653272,0.000009577502,8.52888e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8215612,"threshold_uncertainty_score":0.9144953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02404425159781025,"score_gpt":0.3061933688612142,"score_spread":0.282149117263404,"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."}}