{"id":"W2462667068","doi":"10.13140/2.1.1161.6967","title":"FAST ORTHOPHOTO PRODUCTION USING THE DIGITAL SENSOR SYSTEM","year":2004,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Orthophoto; Photogrammetry; Computer science; Remote sensing; Global Positioning System; Digital mapping; Software; Pixel; Digital camera; Ground sample distance; Digital elevation model; Georeference; Computer vision; Artificial intelligence; Geography","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":[0.00003549844,0.00007613611,0.00006058573,0.00002782531,0.00007096833,0.00007828639,0.00003614716,0.00003073551,0.000003862905],"category_scores_gemma":[0.000008336192,0.00005257568,0.00002745838,0.0001390241,0.0000134461,0.00008848418,0.000005904477,0.00004757727,0.00002630682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009915338,"about_ca_system_score_gemma":0.00000882842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001987914,"about_ca_topic_score_gemma":0.000006105923,"domain_scores_codex":[0.9995798,0.000004602421,0.0001156041,0.00009038734,0.00009737741,0.0001122475],"domain_scores_gemma":[0.9997823,0.000004734125,0.00001211454,0.0001458634,0.00003006178,0.00002495724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001075757,0.000004367809,0.00007314875,0.00003001594,0.000008116547,0.000002333859,0.00007041136,0.9941747,0.004257868,0.001071869,0.000023075,0.0002830305],"study_design_scores_gemma":[0.0002114533,0.00001463375,0.0001492092,0.0000670173,0.00001842126,0.00009530303,0.00132176,0.9711798,0.02604807,0.00003387869,0.0006499661,0.0002104888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.629383,0.00002027827,0.3655888,0.00006710782,0.0005103371,0.0001753074,0.000002353249,0.0003591702,0.003893643],"genre_scores_gemma":[0.9984211,0.000002364642,0.001258946,0.0000107243,0.0001397092,0.000001872989,0.000005587315,0.00002077929,0.0001388625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3690382,"threshold_uncertainty_score":0.2143974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01090621435703863,"score_gpt":0.1892113959082564,"score_spread":0.1783051815512177,"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."}}