{"id":"W4391094969","doi":"10.1109/bigdata59044.2023.10386990","title":"Identifying Regions of High Demand for Transportation Services based on Cluster Evolution and Graph Analysis","year":2023,"lang":"en","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cluster (spacecraft); Graph; Graph theory; Theoretical computer science; Mathematics; Combinatorics; Computer network","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":[0.0007655319,0.00005384045,0.0001414954,0.0004797466,0.0004034111,0.00003221655,0.00007008167,0.00005648825,0.00007766338],"category_scores_gemma":[0.00002681634,0.00005114468,0.0001480745,0.001697705,0.00008952106,0.0001172011,0.000001724788,0.00002524754,0.00000240422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002486996,"about_ca_system_score_gemma":0.00003616648,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01761077,"about_ca_topic_score_gemma":0.2562115,"domain_scores_codex":[0.9991907,0.00009417269,0.000193578,0.0001866089,0.0002190431,0.0001159033],"domain_scores_gemma":[0.9993455,0.0002850227,0.00008270863,0.000115308,0.000126302,0.00004512926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002574697,0.0003780298,0.3647139,0.0009955049,0.001454708,0.000001222538,0.04288869,0.3223698,0.0002875851,0.2600237,0.0007456302,0.005883716],"study_design_scores_gemma":[0.0006466794,0.00006121812,0.7484066,0.00004948864,0.00179365,6.212314e-9,0.01594899,0.1950805,0.0001336579,0.03742221,0.0002632769,0.0001936567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7127671,0.00001418131,0.2852654,0.001393527,0.0000275138,0.0002211356,0.00003372235,0.00006553982,0.0002118985],"genre_scores_gemma":[0.9990433,0.00001709337,0.0002582056,0.00009194693,0.00002307936,0.0000325712,0.0002223906,0.000003272815,0.0003081386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3836928,"threshold_uncertainty_score":0.9889311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02210452587663865,"score_gpt":0.3061299366257683,"score_spread":0.2840254107491296,"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."}}