{"id":"W2119886822","doi":"10.1109/crv.2006.11","title":"An Information-Theoretic Approach to Georegistration of Digital Elevation Maps","year":2006,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital elevation model; Robustness (evolution); Computer science; Morse code; Elevation (ballistics); Artificial intelligence; Mutual information; ENCODE; Measure (data warehouse); Computer vision; Mathematics; Pattern recognition (psychology); Algorithm; Data mining; Geography; Geometry; Remote sensing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001414499,0.0005732073,0.0007779737,0.001906897,0.0004841439,0.001122651,0.001145949,0.0008189565,0.0007937363],"category_scores_gemma":[0.005470473,0.0004008752,0.0008935354,0.00162156,0.001686751,0.00240202,0.002058716,0.001198403,0.0004162633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007070848,"about_ca_system_score_gemma":0.0005373381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004600034,"about_ca_topic_score_gemma":0.0004779923,"domain_scores_codex":[0.9987304,0.0004020774,0.00008594628,0.0001993554,0.0005276942,0.00005453142],"domain_scores_gemma":[0.9988905,0.0004150271,0.0001929034,0.000298101,0.0001590089,0.00004454929],"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":[0.00007573682,0.00005122904,0.0005146389,0.0001868074,0.0001080322,0.0002203868,0.0002419601,0.4219275,0.01678338,0.3659333,0.001400293,0.1925568],"study_design_scores_gemma":[0.00001126126,0.000146872,0.0005120572,0.00003162101,0.0000293873,0.0002972334,0.00005906462,0.7975897,0.009649504,0.1840041,0.007612786,0.00005641405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001811785,0.000117184,0.9974712,0.00006906388,0.0000165725,0.000006605874,0.00001353444,0.00004394525,0.0004501188],"genre_scores_gemma":[0.2787529,0.0008785736,0.7175195,0.0001449983,0.000288886,0.00009103276,0.0001832554,0.0001235242,0.002017426],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001906897,"threshold_uncertainty_score":0.007480621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004388959650960115,"score_gpt":0.1738563507774525,"score_spread":0.1694673911264924,"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."}}