{"id":"W2795976264","doi":"10.3390/rs10040575","title":"Surveying Drifting Icebergs and Ice Islands: Deterioration Detection and Mass Estimation with Aerial Photogrammetry and Laser Scanning","year":2018,"lang":"en","type":"article","venue":"Remote Sensing","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Carleton University","funders":"","keywords":"Iceberg; Photogrammetry; Remote sensing; Global Positioning System; Point cloud; Geodesy; Geology; Structure from motion; Laser scanning; Environmental science; Computer science; Ice sheet; Computer vision; Laser; Motion estimation; Oceanography; Telecommunications; Optics","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":[0.0004902189,0.000125275,0.0001264768,0.00005431939,0.0004957007,0.0002748352,0.00001744072,0.00006625646,0.000006585945],"category_scores_gemma":[0.00007816224,0.0001003209,0.00000905632,0.0001649221,0.0001028565,0.0003143963,0.000007130147,0.00009488301,0.000002394453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004565233,"about_ca_system_score_gemma":0.000009603332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003335505,"about_ca_topic_score_gemma":0.0107546,"domain_scores_codex":[0.9991655,0.0001292882,0.0001318306,0.000256429,0.0001196009,0.0001972969],"domain_scores_gemma":[0.9996162,0.0001043303,0.00008048896,0.00006508114,0.00005608387,0.00007783349],"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":[0.00009533606,6.322773e-7,0.02625056,0.00002970354,0.000009421909,0.000006640435,0.0009144021,0.00007279183,0.01774887,5.866316e-8,0.000001142543,0.9548705],"study_design_scores_gemma":[0.0003706921,0.0001772604,0.1129875,0.0001397544,0.0000210635,0.0001715105,0.0006607216,0.8812407,0.003940858,0.00004558572,0.00004571863,0.0001986111],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759844,0.0001329082,0.02318367,0.00001734962,0.000135159,0.00009344216,0.000002769498,0.00005569783,0.0003945851],"genre_scores_gemma":[0.9795058,0.00002100892,0.02023962,0.00003857362,0.0001535669,6.600573e-9,0.00001757374,0.000005737983,0.0000181232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9546718,"threshold_uncertainty_score":0.6001319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01325365038529894,"score_gpt":0.2137850141888297,"score_spread":0.2005313638035308,"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."}}