{"id":"W4405519045","doi":"10.2316/j.2025.201-0482","title":"VIRTUAL REALITY SCENE RENDERING AND INTERACTION TECHNOLOGY BASED ON MACHINE LEARNING AND SEMI-SUPERVISED LEARNING, 272-283.","year":2024,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Rendering (computer graphics); Computer science; Virtual reality; Human–computer interaction; Artificial intelligence; Computer vision; Computer graphics (images)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009677555,0.0005253878,0.0005442265,0.0009615233,0.0003899013,0.001667216,0.0009866483,0.0006102395,0.006286046],"category_scores_gemma":[0.002740994,0.0006718961,0.0007153653,0.0006603078,0.0008012173,0.001753627,0.0007763422,0.0008692688,0.002434619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000563602,"about_ca_system_score_gemma":0.0004941049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003407745,"about_ca_topic_score_gemma":0.008312338,"domain_scores_codex":[0.9993857,0.0001877787,0.00003248741,0.0001104188,0.0002468158,0.00003669948],"domain_scores_gemma":[0.9991793,0.0004188567,0.00002950527,0.0001330439,0.0002051256,0.00003411793],"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":[0.0003639723,0.0001999073,0.001574526,0.0002818833,0.00009191294,0.0001397136,0.0001947052,0.06782283,0.02758395,0.02851046,0.02419144,0.8490447],"study_design_scores_gemma":[0.00002841183,0.0001344824,0.004232777,0.00004052262,0.00005266319,0.0003956567,0.0001292162,0.899938,0.04039957,0.02619284,0.02840821,0.00004779834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007595721,0.001215738,0.9815169,0.0003266619,0.0001005888,0.00004212422,0.0002006113,0.00188287,0.007118762],"genre_scores_gemma":[0.2734837,0.002888172,0.7010462,0.0001194386,0.0001572334,0.00009053195,0.0008657432,0.0007326014,0.02061639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006286046,"threshold_uncertainty_score":0.02102894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01014566084332653,"score_gpt":0.2396737585997091,"score_spread":0.2295280977563826,"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."}}