{"id":"W4410191620","doi":"10.2139/ssrn.5246895","title":"Lidar-3dgs Lidar Reinforcement for Multimodal Initialization of 3d Gaussian Splats","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Lidar; Initialization; Gaussian; Remote sensing; Computer science; Reinforcement; Artificial intelligence; Geology; Computer vision; Engineering; Physics; Structural 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":[0.0006214197,0.0007507867,0.0005606816,0.0004332107,0.0004219713,0.0006274236,0.001138736,0.001195303,0.00568482],"category_scores_gemma":[0.002719357,0.0004591317,0.0004850615,0.0003108291,0.0005551777,0.0007953581,0.002392021,0.001137636,0.001265814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006716084,"about_ca_system_score_gemma":0.001057151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004079204,"about_ca_topic_score_gemma":0.006586229,"domain_scores_codex":[0.9996212,0.00007117013,0.0000171853,0.00008135623,0.000149974,0.0000590664],"domain_scores_gemma":[0.9993081,0.0001976947,0.00007409927,0.0001499498,0.0001899932,0.00008018217],"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":[0.0004627037,0.0001438801,0.002183114,0.0001016987,0.00003310501,0.0001739316,0.0002028845,0.7268482,0.03476902,0.007834444,0.003041327,0.2242057],"study_design_scores_gemma":[0.000006367561,0.00001872048,0.00009201265,0.00000419883,0.000001488574,0.00001333228,0.000007601489,0.9959441,0.0028414,0.0006046933,0.0004626583,0.000003430491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03290474,0.00006417085,0.9630387,0.0001289684,0.00004734722,0.00006232437,0.00006858845,0.001731697,0.001953572],"genre_scores_gemma":[0.614917,0.00003340877,0.3819245,0.0001094427,0.00002378234,0.0001081075,0.0002210156,0.0003463907,0.002316375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00568482,"threshold_uncertainty_score":0.01901764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01171827470625835,"score_gpt":0.2867398672707054,"score_spread":0.275021592564447,"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."}}