{"id":"W4395047885","doi":"10.21203/rs.3.rs-4281942/v1","title":"VoxelFSD: voxel-based fully sparse detector with sparse convolution for 3D object detection","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Education and Child Care","funders":"Government of Jiangsu Province","keywords":"Convolution (computer science); Artificial intelligence; Detector; Computer science; Voxel; Object (grammar); Pattern recognition (psychology); Computer vision; Artificial neural network","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":[0.001041981,0.00107861,0.001448085,0.001429471,0.0004197607,0.001488314,0.002354176,0.001922984,0.007461367],"category_scores_gemma":[0.003560925,0.001182427,0.001138922,0.00165283,0.0006555929,0.001500019,0.002760757,0.001561854,0.004692124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006260193,"about_ca_system_score_gemma":0.001891789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003689854,"about_ca_topic_score_gemma":0.007229412,"domain_scores_codex":[0.9990516,0.0001621064,0.0000406183,0.0001395134,0.0005138095,0.00009234376],"domain_scores_gemma":[0.9990809,0.0002911882,0.00006752437,0.0002476276,0.000233045,0.00007968253],"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":[0.0005882975,0.0001403887,0.001025496,0.0003168721,0.0002506149,0.0002226291,0.0001380632,0.06875524,0.05824076,0.01886416,0.0478763,0.8035812],"study_design_scores_gemma":[0.00004676062,0.00006076963,0.0003338116,0.00001830977,0.00002543282,0.0003824013,0.00002176783,0.9418741,0.03018537,0.01406532,0.01295274,0.0000330755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001285674,0.00009751825,0.9932706,0.00007630418,0.00003447137,0.00003218882,0.0002345576,0.004635325,0.0003334469],"genre_scores_gemma":[0.02908832,0.0001535227,0.9666921,0.000133695,0.00003930588,0.0001254941,0.001083161,0.0007492108,0.001935182],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007461367,"threshold_uncertainty_score":0.02496076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06763481634759909,"score_gpt":0.3866355715863989,"score_spread":0.3190007552387998,"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."}}