{"id":"W1966975618","doi":"10.5194/isprsarchives-xxxix-b1-277-2012","title":"3D PHOTOGRAMMETRIC PROCESSING OF WORLDVIEW-2 DATA WITHOUT GCP","year":2012,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Photogrammetry; Stereoscopy; Metadata; Remote sensing; Lidar; Elevation (ballistics); Data collection; Computer science; Altimeter; Computer vision; Artificial intelligence; Geography; Geology; Mathematics; Statistics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002308493,0.0005747979,0.0006410658,0.001450967,0.001066022,0.0007722261,0.002728581,0.0001328918,0.00001115272],"category_scores_gemma":[0.0008866572,0.0003770327,0.0003491441,0.002144257,0.003218729,0.001060006,0.001277331,0.0006336988,0.000003964964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005223383,"about_ca_system_score_gemma":0.0002325712,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5788172,"about_ca_topic_score_gemma":0.06884597,"domain_scores_codex":[0.9944428,0.0002763354,0.001909877,0.0004437442,0.0021177,0.0008095081],"domain_scores_gemma":[0.9958122,0.001025456,0.001702506,0.0008521589,0.0003626208,0.0002449949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001046006,0.00003387517,0.001296978,0.0001826124,0.0001265049,1.745277e-7,0.003167724,0.002163085,0.002724807,0.000002002368,0.00005879513,0.9901388],"study_design_scores_gemma":[0.0006859881,0.00008056268,0.002867384,0.0006073879,0.00009787086,0.0001474322,0.001649838,0.969754,0.01333199,0.001082703,0.009276947,0.000417946],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009529836,0.0004473952,0.9751987,0.0007734402,0.002335269,0.0006984489,0.0001876948,0.0001091579,0.01072004],"genre_scores_gemma":[0.9883975,0.0005048093,0.0101552,0.000553199,0.0002260919,5.945817e-7,0.00008350721,0.00002604153,0.00005309358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9897209,"threshold_uncertainty_score":0.9998682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02823646408173941,"score_gpt":0.2726018774457123,"score_spread":0.2443654133639729,"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."}}