{"id":"W4393551759","doi":"10.5281/zenodo.7879595","title":"Higher-order Mobility Flow Data","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Flow (mathematics); Order (exchange); Environmental science; Mechanics; Physics; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005302886,0.0009768081,0.0005649558,0.00188828,0.000494397,0.0007967113,0.001184064,0.0009788343,0.008916712],"category_scores_gemma":[0.002490342,0.0002355128,0.0007324646,0.003047029,0.000267632,0.0007849475,0.0008742656,0.001155278,0.009752627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007161266,"about_ca_system_score_gemma":0.0009986887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01503518,"about_ca_topic_score_gemma":0.02199136,"domain_scores_codex":[0.9994994,0.00008019438,0.00005507791,0.0001356559,0.000146851,0.00008280026],"domain_scores_gemma":[0.9993116,0.0001214988,0.00006325688,0.0002125565,0.0002283957,0.00006277121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004515166,0.000322263,0.01984787,0.0009927526,0.0001364756,0.0003682431,0.0002701322,0.01926482,0.002494081,0.006900355,0.8981892,0.05076223],"study_design_scores_gemma":[0.0002195991,0.0001250997,0.04894089,0.0003101638,0.00006358843,0.0006297038,0.0005922991,0.03211974,0.005474002,0.007574646,0.9038137,0.0001367217],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02077771,0.0001789791,0.005578496,0.0003279826,0.0001482882,0.0001325084,0.9651591,0.003058563,0.004638421],"genre_scores_gemma":[0.02034813,0.0001120824,0.005030212,0.00006360046,0.00002153894,0.0001873183,0.972453,0.0001203094,0.001663814],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01503518,"threshold_uncertainty_score":0.02989537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05182098167095657,"score_gpt":0.2588347043882134,"score_spread":0.2070137227172569,"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."}}