{"id":"W4313397047","doi":"10.1049/ipr2.12729","title":"A survey on end‐to‐end point cloud learning","year":2022,"lang":"en","type":"article","venue":"IET Image Processing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Point cloud; Computer science; Cloud computing; Deep learning; Segmentation; Artificial intelligence; Focus (optics); Point (geometry); Domain (mathematical analysis); End-to-end principle; Data mining; Machine learning; Data science; Tracking (education)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000733063,0.0001130684,0.0001035045,0.00004000304,0.000854528,0.0001089602,0.0001990127,0.00001880277,0.001556183],"category_scores_gemma":[0.0001092576,0.0001165669,0.00003273409,0.0004803131,0.00007617475,0.00009969412,0.0002446418,0.000334018,0.0007752154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001769848,"about_ca_system_score_gemma":0.00002266244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006327947,"about_ca_topic_score_gemma":0.00005104092,"domain_scores_codex":[0.9986724,0.0001566824,0.0001499529,0.0003661492,0.000386641,0.0002682043],"domain_scores_gemma":[0.9995537,0.00006819191,0.00007479537,0.0001947254,0.00001024989,0.00009832776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007587486,0.0002648264,0.00964716,0.00001734687,0.000008824332,0.00002700335,0.005412453,0.02904431,0.1021426,0.00001046843,0.03016597,0.8231832],"study_design_scores_gemma":[0.001400127,0.0009137341,0.4731346,0.0001093066,0.00005408606,0.000167721,0.004832059,0.07659037,0.03138277,0.001297034,0.4078908,0.002227474],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.909269,0.00005680914,0.01182476,0.001972671,0.0001901158,0.0003273579,0.00003365177,0.0002786506,0.07604695],"genre_scores_gemma":[0.9939301,0.000001064019,0.00356486,0.0006711947,0.00004320556,0.000008272696,0.00003423597,0.00002078757,0.001726269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8209557,"threshold_uncertainty_score":0.9993565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461046973289131,"score_gpt":0.2596159498532288,"score_spread":0.2450054801203375,"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."}}