{"id":"W6966495929","doi":"10.48448/qf09-7q95","title":"X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-Modal Knowledge Transfer","year":2024,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Point cloud; Segmentation; Inference; Transformer; Cloud computing; Transfer of learning; Semantics (computer science); Knowledge transfer","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001131022,0.0008274201,0.0006485009,0.001175755,0.0005659392,0.002208343,0.004268896,0.0005445761,0.0002346958],"category_scores_gemma":[0.0001208897,0.0006620873,0.0002165439,0.002800531,0.001811147,0.001251783,0.0008222185,0.001167973,0.0006155115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001348813,"about_ca_system_score_gemma":0.001213644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001787241,"about_ca_topic_score_gemma":0.000239839,"domain_scores_codex":[0.9944176,0.00007063067,0.0006421248,0.002219097,0.001405371,0.001245171],"domain_scores_gemma":[0.9976876,0.0001023815,0.0001910118,0.001542056,0.000201651,0.0002752864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002247876,0.0002249498,0.000002214765,0.0004795714,0.00006129633,0.00007408761,0.002599521,0.00001651537,0.006195431,0.9301936,0.03823418,0.02189612],"study_design_scores_gemma":[0.001459772,0.001093579,0.000002445927,0.007239352,0.0001122989,0.0001533113,0.0004059668,0.03221165,0.2021006,0.6664036,0.0848347,0.003982722],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002614003,0.004305173,0.8032018,0.0007353885,0.002922058,0.0005416116,0.00003125098,0.002875139,0.1853615],"genre_scores_gemma":[0.2583374,0.0003563713,0.5796767,0.001893054,0.002282221,0.00009601237,0.00003510225,0.0009212916,0.1564018],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.26379,"threshold_uncertainty_score":0.9995831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03791698760271094,"score_gpt":0.3456183589797978,"score_spread":0.3077013713770869,"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."}}