{"id":"W4400248771","doi":"10.23967/isc.2024.084","title":"Combining Remote Sensing Techniques to Optimize Digital Surface Models for Change Detection – A Case Study at a Pit Wall in the Canadian Cordillera","year":2024,"lang":"en","type":"article","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Remote sensing; Digital surface; Change detection; Computer science; Surface (topology); Geology; Environmental science; Lidar; Geometry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0009464163,0.0009437712,0.0004032366,0.000997549,0.0006049927,0.001489909,0.0009813738,0.0006331007,0.0006667557],"category_scores_gemma":[0.001324011,0.0003497355,0.000614638,0.00125169,0.0004502098,0.0004704023,0.0006704208,0.0003857737,0.000188337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003378362,"about_ca_system_score_gemma":0.002653154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4605049,"about_ca_topic_score_gemma":0.5337002,"domain_scores_codex":[0.9995184,0.00005127714,0.00002503127,0.00009257239,0.0002342844,0.00007852269],"domain_scores_gemma":[0.9996384,0.0001083348,0.00003406941,0.00004700803,0.000149939,0.00002222036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001822321,0.0002776957,0.02730472,0.0001477217,0.00008211009,0.0003487756,0.0003868818,0.8004237,0.01738361,0.000903028,0.0005558475,0.1520039],"study_design_scores_gemma":[0.000009842624,0.00007038363,0.01215443,0.000007983504,0.00002362566,0.00003822067,0.0001768176,0.9810833,0.005386287,0.0001360808,0.000892026,0.00002101378],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950691,0.0001935446,0.04430299,0.0001481027,0.00001081486,0.0001856505,0.0003587281,0.0007222056,0.003386985],"genre_scores_gemma":[0.9451132,0.00008339671,0.05341985,0.00001852001,0.000002237538,0.00003923619,0.0003565837,0.00006591078,0.0009010049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5394951,"threshold_uncertainty_score":0.9156491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05970752626264748,"score_gpt":0.27247392550023,"score_spread":0.2127663992375825,"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."}}