{"id":"W4408325091","doi":"10.1109/globecom52923.2024.10901692","title":"Generative AI Empowered LiDAR Point Cloud Generation with Multimodal Transformer","year":2024,"lang":"en","type":"article","venue":"","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); University of Ottawa","funders":"","keywords":"Lidar; Computer science; Transformer; Point cloud; Generative grammar; Cloud computing; Artificial intelligence; Remote sensing; Engineering; Geology; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002782588,0.0008165035,0.0005191148,0.0005379241,0.0002054766,0.0005890699,0.001115966,0.0006201894,0.002772572],"category_scores_gemma":[0.001028187,0.0003380866,0.0009061301,0.0005510193,0.0003421127,0.0008137073,0.001106001,0.001076549,0.001072334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005445993,"about_ca_system_score_gemma":0.0005826037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005847227,"about_ca_topic_score_gemma":0.01057623,"domain_scores_codex":[0.9998314,0.00002326641,0.000006631382,0.00005463356,0.00005498482,0.00002896651],"domain_scores_gemma":[0.9997725,0.00009314744,0.00001695371,0.00004843032,0.00005194294,0.0000170574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002324366,0.0001337808,0.002209293,0.0001275859,0.00008333905,0.0003194342,0.0001077324,0.5328209,0.02706556,0.007679388,0.005890656,0.4233298],"study_design_scores_gemma":[0.000007099022,0.00001566038,0.0001026359,0.000004024695,0.000006216977,0.00004340052,0.000007481797,0.9938043,0.003568471,0.001777968,0.0006582965,0.000004439985],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03212041,0.0003921715,0.9601362,0.0002441103,0.00007376376,0.00005873942,0.0004611301,0.003687921,0.002825606],"genre_scores_gemma":[0.6957042,0.0003387383,0.2950074,0.0003881635,0.00006397017,0.0001145831,0.002171546,0.000392773,0.005818723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005847227,"threshold_uncertainty_score":0.01162636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857281153029573,"score_gpt":0.2327145320812933,"score_spread":0.2141417205509976,"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."}}