{"id":"W3135107705","doi":"10.3390/ijgi10030157","title":"Computational Geometry-Based Surface Reconstruction for Volume Estimation: A Case Study on Magnitude-Frequency Relations for a LiDAR-Derived Rockfall Inventory","year":2021,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rockfall; Point cloud; Magnitude (astronomy); Photogrammetry; Geology; Lidar; Power law; Geometry; Remote sensing; Computer science; Mathematics; Seismology; Landslide; Statistics; Physics; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005690766,0.0001620081,0.0001937926,0.0002256141,0.000284781,0.0002064841,0.0002157361,0.0001145991,0.0005174787],"category_scores_gemma":[0.0005051075,0.0001495374,0.0002070031,0.0002259008,0.00005171028,0.001978111,0.00004338855,0.0002150436,0.00009134984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005611876,"about_ca_system_score_gemma":0.0002136086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006984764,"about_ca_topic_score_gemma":0.0000273937,"domain_scores_codex":[0.9980132,0.00006077963,0.0009085468,0.0001396839,0.0007074527,0.0001703484],"domain_scores_gemma":[0.9977199,0.0001962241,0.0007826102,0.0001223035,0.001073101,0.0001059025],"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":[0.0004157555,0.0004050126,0.02497208,0.00002402625,0.0002878642,0.0001163718,0.001731938,0.9430895,0.0001031909,0.0003200215,0.003618111,0.02491612],"study_design_scores_gemma":[0.01075432,0.001537162,0.01853055,0.0001937847,0.0002674821,0.005183008,0.005210004,0.9427506,0.0004629527,0.006239667,0.008337438,0.0005330852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6755939,0.00001426161,0.3203988,0.001620893,0.0012771,0.0005126919,0.0001387927,0.00002222398,0.0004213079],"genre_scores_gemma":[0.9456687,0.000003628864,0.05330326,0.0004752884,0.0001102006,0.00002831193,0.000284667,0.00001100778,0.0001149577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2700748,"threshold_uncertainty_score":0.6097957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103748695270599,"score_gpt":0.2637248796925687,"score_spread":0.2526873927398627,"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."}}