{"id":"W4396853536","doi":"10.1109/fnwf58287.2023.10520414","title":"Modeling Local Demand for Mobile Spectrum using Large Crowdsourced Datasets","year":2023,"lang":"en","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Carleton University; Communications Research Centre Canada","funders":"","keywords":"Computer science; Scarcity; Proxy (statistics); Population; Software deployment; Intuition; Mobile device; Machine learning; Economics; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001471565,0.00007664039,0.0001339571,0.0001093168,0.001067383,0.00008847206,0.0001804859,0.00007105902,0.0006416022],"category_scores_gemma":[0.0001083355,0.00007538401,0.00009795975,0.000507682,0.00009135273,0.0001414364,0.00003736941,0.00005747501,0.00009454237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008552931,"about_ca_system_score_gemma":0.0001422979,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007921872,"about_ca_topic_score_gemma":0.03682042,"domain_scores_codex":[0.998846,0.00008897094,0.0001894672,0.0002561055,0.0002270771,0.0003923676],"domain_scores_gemma":[0.9994782,0.0001428346,0.00002658579,0.0002031652,0.00004554888,0.0001036271],"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":[0.00001821033,0.0001006363,0.0005239568,0.00003933121,0.00005781072,0.000002617139,0.006591162,0.9750223,0.0001180411,0.01199521,0.002385941,0.003144742],"study_design_scores_gemma":[0.0001796224,0.00001221051,0.00001668341,0.000006565162,0.00003442493,6.559801e-8,0.01068378,0.9757679,0.00007979463,0.002404576,0.01070427,0.0001101632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3062521,0.0000253351,0.6922759,0.0003197591,0.00005618596,0.000301696,0.0001282006,0.0001622678,0.0004786076],"genre_scores_gemma":[0.9983415,0.0000110922,0.0002895872,0.0001421907,0.0001865025,0.00003836347,0.0003301763,0.000009409298,0.0006511634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6920894,"threshold_uncertainty_score":0.9986845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04535291406692403,"score_gpt":0.3599344505420194,"score_spread":0.3145815364750954,"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."}}