{"id":"W4412164291","doi":"10.1109/memea65319.2025.11067998","title":"Classifying Mobility Aid Use from LiDAR Data","year":2025,"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":"Carleton University","funders":"","keywords":"Lidar; Computer science; Remote sensing; Geology","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":[0.0001989677,0.0006208269,0.000307257,0.00134753,0.0002078012,0.0003974601,0.0005096598,0.0004944039,0.00101395],"category_scores_gemma":[0.001057001,0.0001069124,0.0003591255,0.0009620241,0.0001324732,0.0004951507,0.0007286519,0.0003159076,0.0008395987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002108812,"about_ca_system_score_gemma":0.0003441054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005289918,"about_ca_topic_score_gemma":0.01240337,"domain_scores_codex":[0.9997795,0.00002944275,0.00001655533,0.00005791435,0.00007418288,0.00004239246],"domain_scores_gemma":[0.999759,0.00004194225,0.00003350261,0.00003301392,0.0001143955,0.0000181754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006228783,0.0005262702,0.298533,0.000688118,0.0001744718,0.0008019338,0.0007069291,0.02837572,0.05022306,0.001131028,0.01416393,0.6040527],"study_design_scores_gemma":[0.00007220589,0.0007540152,0.3366053,0.0003385024,0.0001692816,0.001350841,0.004318499,0.5716714,0.05779557,0.004618487,0.02219687,0.0001090785],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9052551,0.000680841,0.07805124,0.000370502,0.00009634155,0.0002854966,0.00943215,0.001559095,0.004269172],"genre_scores_gemma":[0.9627946,0.0003118009,0.02952855,0.00006983933,0.00002367512,0.0001366719,0.006148149,0.00002186823,0.0009648989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005289918,"threshold_uncertainty_score":0.01051825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1177564773343531,"score_gpt":0.3838877756165596,"score_spread":0.2661312982822065,"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."}}