{"id":"W2926918810","doi":"10.3390/rs11070784","title":"Resolving Fine-Scale Surface Features on Polar Sea Ice: A First Assessment of UAS Photogrammetry Without Ground Control","year":2019,"lang":"en","type":"article","venue":"Remote Sensing","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Natural Science Foundation of China; Natural Environment Research Council; Sight Research UK; European Space Agency","keywords":"Photogrammetry; Terrain; Remote sensing; Bundle adjustment; Sea ice; Orientation (vector space); Scale (ratio); Geodesy; Computer science; Geology; Geography; Meteorology; Cartography","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":[0.0005777868,0.0002040437,0.0003563255,0.00004919826,0.0002066771,0.00009675048,0.0001256349,0.0001166798,0.0001415907],"category_scores_gemma":[0.00004584678,0.000158819,0.0001132965,0.0002378649,0.00005159655,0.0001140349,0.00001011015,0.0003193283,0.00006610616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001677565,"about_ca_system_score_gemma":0.00004078783,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01692489,"about_ca_topic_score_gemma":0.01502089,"domain_scores_codex":[0.9984099,0.0001991968,0.0002409957,0.0003412048,0.0004185443,0.0003901357],"domain_scores_gemma":[0.9990225,0.0003444274,0.0001405775,0.0003062193,0.00007042562,0.0001158267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002287942,0.000028283,0.8782377,0.0001915712,0.00009835394,0.00004614117,0.0006326737,0.01894188,0.009209298,0.000003454897,0.0003889812,0.09199292],"study_design_scores_gemma":[0.0007926241,0.0002612188,0.6208246,0.0003422556,0.0000299729,0.0000465332,0.000490621,0.3749179,0.0006160513,0.00002467773,0.00133755,0.0003160053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883112,0.0004275703,0.0004128819,0.0001715031,0.0003737823,0.0002549359,0.00005423151,0.00006460679,0.009929289],"genre_scores_gemma":[0.9918671,0.00001921607,0.006984566,0.0001505627,0.00007635674,2.483217e-9,0.00006118332,0.00000953439,0.0008314408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.355976,"threshold_uncertainty_score":0.9896215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117684124689842,"score_gpt":0.2382998153013466,"score_spread":0.2271229740544482,"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."}}