{"id":"W3159132778","doi":"10.18280/mmep.080209","title":"Modelling Trip Distribution Using the Gravity Model and Fratar's Method","year":2021,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Urban Transport Systems Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trip distribution; Gravity model of trade; Distribution (mathematics); Process (computing); Econometrics; Trip generation; Sample (material); Computer science; TRIPS architecture; Transport engineering; Operations research; Mathematics; Engineering; 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":[0.0004769214,0.0002677185,0.0004044581,0.00004810146,0.0001367879,0.0001218948,0.00008637108,0.000134946,0.000003853076],"category_scores_gemma":[0.00001177837,0.0002190672,0.00009101068,0.0002320181,0.00002265229,0.0001291525,0.00002935322,0.0003170926,0.000001381547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004214513,"about_ca_system_score_gemma":0.00001248179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003389489,"about_ca_topic_score_gemma":0.000001706175,"domain_scores_codex":[0.9987056,0.00002121215,0.0004302748,0.0002935072,0.0002068269,0.0003425972],"domain_scores_gemma":[0.9993768,0.0001168344,0.00003135169,0.0002872407,0.00005579254,0.0001320263],"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":[8.063923e-7,0.00001211854,0.000005219943,0.0006465362,0.00007904493,0.000003302514,0.0004630609,0.9923209,0.001171124,0.00519939,0.000004189487,0.00009429961],"study_design_scores_gemma":[0.0001198211,0.000004594696,5.995877e-7,0.0002051637,0.0001594718,0.00003942535,0.00003709846,0.9878997,0.0003874333,0.01082088,0.00007016025,0.0002556124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1008027,0.001558728,0.8971661,0.00003203159,0.0000430459,0.0001283676,0.00001935665,0.0002154752,0.00003412145],"genre_scores_gemma":[0.8154387,0.0001572608,0.1842394,0.000004440793,0.00003808992,0.00002017244,0.00001749886,0.00005156589,0.0000328505],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.714636,"threshold_uncertainty_score":0.8933303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03418777253751396,"score_gpt":0.2208673019940571,"score_spread":0.1866795294565431,"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."}}