{"id":"W6944944696","doi":"10.2312/pg.20241279","title":"PVP-SSD: Point-Voxel Fusion with Partitioned Point Cloud Sampling for Anchor-Free Single-Stage Small 3D Object Detection","year":2024,"lang":"en","type":"article","venue":"Singapore Management University Institutional Knowledge (InK) (Singapore Management University)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Point cloud; Object detection; Sampling (signal processing); Object (grammar); Convolution (computer science); Feature (linguistics); Feature extraction; Pattern recognition (psychology)","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":[0.000569127,0.001169752,0.00128804,0.001480273,0.0004941921,0.0009994308,0.002055165,0.0008538402,0.002403172],"category_scores_gemma":[0.001801463,0.0005604824,0.001133724,0.001757877,0.0004941186,0.001814188,0.0029187,0.001043733,0.001558716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004655442,"about_ca_system_score_gemma":0.001072224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003975019,"about_ca_topic_score_gemma":0.006191315,"domain_scores_codex":[0.9992589,0.00006007076,0.00002778546,0.0001835352,0.000374299,0.00009540214],"domain_scores_gemma":[0.9994463,0.0001187749,0.00005007719,0.0001403283,0.0001952756,0.00004926026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003626352,0.0001775817,0.005335968,0.0001584447,0.0001590979,0.0003056404,0.0002116051,0.06486645,0.08348724,0.004314424,0.006860529,0.8337604],"study_design_scores_gemma":[0.00002052591,0.00009599375,0.001892827,0.000009213778,0.0000274478,0.0002900339,0.00006227904,0.9605522,0.02795295,0.005336377,0.003735636,0.00002461257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01473515,0.0001447907,0.9820222,0.00005448777,0.00002862705,0.00007344203,0.0002062923,0.002214626,0.0005204732],"genre_scores_gemma":[0.2630316,0.0002496192,0.732231,0.0001377442,0.000058716,0.0001899827,0.001928172,0.0003219348,0.001851189],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003975019,"threshold_uncertainty_score":0.008039415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02140218269589369,"score_gpt":0.2083951359322264,"score_spread":0.1869929532363327,"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."}}