{"id":"W4387402950","doi":"10.1016/j.jag.2023.103512","title":"Global automated extraction of bathymetric photons from ICESat-2 data based on a PointNet++ model","year":2023,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Wilfrid Laurier University","funders":"Canadian Space Agency","keywords":"Bathymetry; Computer science; Remote sensing; Seafloor spreading; Segmentation; Artificial intelligence; Geography; Geology; Cartography; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004261129,0.00009533457,0.0001220219,0.0001897071,0.000062417,0.00006154042,0.000302159,0.00006348878,0.00007884888],"category_scores_gemma":[0.00007706709,0.0000885729,0.00003730013,0.0005585753,0.00004507374,0.0006608717,0.00007561622,0.00009181228,0.00008369322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000661462,"about_ca_system_score_gemma":0.00004204594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001464855,"about_ca_topic_score_gemma":0.00004032053,"domain_scores_codex":[0.9985414,0.00001379659,0.0005363323,0.0001304781,0.0006823789,0.00009560436],"domain_scores_gemma":[0.9989333,0.00009798285,0.0005943303,0.0002156513,0.00009649034,0.00006223462],"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":[0.0002525178,0.00008940807,0.003407422,0.000007018867,0.00004398689,0.000001697059,0.0003753695,0.8978634,0.004629638,0.000468169,0.005335062,0.08752628],"study_design_scores_gemma":[0.0005051357,0.0000238799,0.1897263,0.0000179303,0.00001318068,0.000003987896,0.00007763122,0.8058535,0.0005819931,0.000742454,0.002390913,0.00006301802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9585141,0.000003541709,0.03200914,0.0007993334,0.0002016186,0.0001599642,0.0001736539,0.00009608562,0.00804259],"genre_scores_gemma":[0.9837245,0.00003174685,0.01514995,0.0004086101,0.00004565763,0.000001123228,0.0006049538,0.000005367863,0.00002808985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1863189,"threshold_uncertainty_score":0.3611898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03240698646332217,"score_gpt":0.2883605007777029,"score_spread":0.2559535143143807,"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."}}