{"id":"W7092670511","doi":"10.2312/pg.20251287","title":"Unsupervised 3D Shape Parsing with Primitive Correspondence","year":2025,"lang":"","type":"article","venue":"Eurographics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Parsing; Set (abstract data type); Segmentation; Process (computing); Pattern recognition (psychology); Computer graphics; Task (project management); Unsupervised learning","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":[0.001040594,0.001724595,0.002048574,0.003233119,0.0009831191,0.002078504,0.003364156,0.002343582,0.003843267],"category_scores_gemma":[0.004276285,0.001701693,0.003272186,0.003216393,0.001567136,0.002308532,0.003341804,0.002554454,0.003616137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008495083,"about_ca_system_score_gemma":0.001695354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00325605,"about_ca_topic_score_gemma":0.006224704,"domain_scores_codex":[0.9979525,0.0003162138,0.0001037145,0.0007020149,0.0007907423,0.0001347564],"domain_scores_gemma":[0.9972076,0.0006636656,0.0002284015,0.001350054,0.0004490839,0.0001012687],"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":[0.0003040304,0.0001963394,0.002167384,0.0002141186,0.0002120341,0.0002611411,0.0003566812,0.3236413,0.04358682,0.01681096,0.00900646,0.6032426],"study_design_scores_gemma":[0.00001140397,0.00002918546,0.0002915226,0.00001185491,0.00001687267,0.0001597285,0.0000335177,0.9780089,0.009278977,0.009685261,0.002452143,0.00002064067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004371379,0.00004642324,0.9921749,0.00003369934,0.00001217092,0.00003918986,0.00009073095,0.002790637,0.0004408574],"genre_scores_gemma":[0.1204878,0.0001572253,0.8742948,0.0001286869,0.00003207094,0.0001610577,0.001687173,0.001161657,0.001889557],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003843267,"threshold_uncertainty_score":0.01285702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112939417460957,"score_gpt":0.2287562887451632,"score_spread":0.2176268945705537,"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."}}