{"id":"W4415371177","doi":"10.5194/ica-adv-5-15-2025","title":"Urban Planning Analysis Using Stereo Mapping Feature Collection","year":2025,"lang":"en","type":"article","venue":"Advances in Cartography and GIScience of the ICA","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Langara College","funders":"","keywords":"Metropolitan area; Geospatial analysis; Urban planning; Feature (linguistics); Perspective (graphical); Population; Focus (optics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002323871,0.00007664782,0.0001559202,0.0004252484,0.0002851114,0.00003690415,0.0001597843,0.00003806559,0.000004554133],"category_scores_gemma":[0.00002702308,0.00004874339,0.00009039197,0.003813897,0.0002389367,0.0002096199,0.00001487111,0.0001080846,7.883164e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002464802,"about_ca_system_score_gemma":0.00002373216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005270357,"about_ca_topic_score_gemma":0.001417675,"domain_scores_codex":[0.9992997,0.00006121938,0.0001319461,0.0002004144,0.0001435506,0.0001631568],"domain_scores_gemma":[0.9996278,0.00009651316,0.00007807207,0.0001508163,0.00002007558,0.00002668643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001163679,0.000003466338,0.9684598,0.00001276144,0.00001818041,8.559001e-7,0.0004449953,0.02007041,0.00007099706,0.0000193916,0.00003133615,0.0108561],"study_design_scores_gemma":[0.0001172522,0.0000198538,0.9428977,0.0001337418,0.0000595473,0.000002935843,0.0006216718,0.05177756,0.0001597303,0.0007309533,0.00339538,0.00008366316],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840207,0.00747323,0.0008623153,0.0001736719,0.0003587623,0.00007725621,0.000006775418,0.000009589522,0.007017745],"genre_scores_gemma":[0.9980282,0.0002746446,0.001522903,0.00007232178,0.00001251472,7.885072e-8,0.000001531184,6.201464e-7,0.00008719855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03170715,"threshold_uncertainty_score":0.2192875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009175253608411859,"score_gpt":0.2457482624746896,"score_spread":0.2365730088662777,"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."}}