{"id":"W3154077890","doi":"10.24908/iqurcp.10296","title":"Best Practices in Low Altitude UAV Mapping for GIS Applications","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orthophoto; Photogrammetry; Computer science; Aerial survey; Flight planning; Aerial photography; Remote sensing; Mobile mapping; GNSS applications; Metric (unit); Computer vision; Global Positioning System; Geography; Operations management; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01046054,0.00137642,0.0007853298,0.003795105,0.001545083,0.00840079,0.005625785,0.002643161,0.003995102],"category_scores_gemma":[0.02547975,0.001304033,0.001015728,0.004844141,0.003156616,0.005360054,0.003368935,0.002978472,0.005721172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001972411,"about_ca_system_score_gemma":0.001866101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005054224,"about_ca_topic_score_gemma":0.006547554,"domain_scores_codex":[0.9860395,0.004428074,0.001459119,0.001352093,0.006310925,0.0004103677],"domain_scores_gemma":[0.9836559,0.003985445,0.0008983426,0.005725886,0.005375226,0.000359121],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005175861,0.000262877,0.003468165,0.001620092,0.0001019447,0.0007121821,0.00458552,0.02923728,0.01320887,0.09117547,0.02354347,0.8320324],"study_design_scores_gemma":[0.00005234523,0.000266414,0.006527311,0.003876121,0.0001036267,0.002207888,0.004888045,0.05734049,0.03349419,0.2255943,0.6653913,0.000257919],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004780956,0.003653358,0.9580854,0.00320923,0.0002423964,0.0004834946,0.0002257416,0.002976927,0.02634244],"genre_scores_gemma":[0.03378279,0.002800549,0.9578705,0.0002784348,0.00006207864,0.0002000205,0.0003540095,0.00050192,0.004149784],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01046054,"threshold_uncertainty_score":0.05532128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2515394218189615,"score_gpt":0.4067103168426313,"score_spread":0.1551708950236698,"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."}}