{"id":"W4378745485","doi":"10.3389/frobt.2023.1184614","title":"Point cloud completion in challenging indoor scenarios with human motion","year":2023,"lang":"en","type":"review","venue":"Frontiers in Robotics and AI","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Point cloud; Computer vision; Iterative closest point; Artificial intelligence; Perspective (graphical); Transformation (genetics); Rigid transformation; Point (geometry); Transformation matrix; Trajectory; Series (stratigraphy); Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002110189,0.0003468572,0.0009900671,0.0006330322,0.00006512496,0.00007041772,0.0001100378,0.0002802371,0.000002026848],"category_scores_gemma":[0.00001036893,0.0003233705,0.00007349661,0.0004951719,0.00003745449,0.00006991003,0.00003077941,0.0005184179,0.000004397503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002404023,"about_ca_system_score_gemma":0.00002036512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002395492,"about_ca_topic_score_gemma":0.00007038865,"domain_scores_codex":[0.9986046,0.00006058534,0.0005396139,0.0003072429,0.0001634525,0.0003245238],"domain_scores_gemma":[0.9996035,0.00002343659,0.00008543669,0.0001974884,0.00002441235,0.00006577765],"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":[0.000001800166,0.00002534203,0.0001866565,0.007295765,0.000053556,0.00003802075,0.00009340304,0.935451,2.098263e-7,0.001213193,0.0005677473,0.05507333],"study_design_scores_gemma":[0.0007404378,0.0000633089,0.0001353914,0.01813876,0.0001788361,0.00001259643,0.0001526823,0.9464418,4.349689e-7,0.0005524841,0.0327555,0.0008277817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002740214,0.6392513,0.358903,0.0000485262,0.0009000657,0.0006422419,0.00001074403,0.000137247,0.00007945517],"genre_scores_gemma":[0.001123142,0.9954851,0.002745347,0.00001459683,0.0001455449,0.00002706506,0.000289654,0.0001315263,0.00003806797],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3562338,"threshold_uncertainty_score":0.9999219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03082789584891906,"score_gpt":0.2641545796106312,"score_spread":0.2333266837617121,"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."}}