{"id":"W2025973801","doi":"10.1145/2816795.2818073","title":"Deep points consolidation","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Science and Technology Planning Project of Guangdong Province; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Consolidation (business); Topological skeleton; Surface (topology); Point (geometry); Geometry; Representation (politics); Medial axis; Artificial intelligence; Computer science; Mathematics; Skeleton (computer programming); Algorithm; Segmentation; Active shape model","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":[],"consensus_categories":[],"category_scores_codex":[0.00007239241,0.0001110913,0.0001180861,0.0001938562,0.00004892434,0.00001393058,0.0001565806,0.00007489289,0.00003535514],"category_scores_gemma":[0.0000258124,0.0001128791,0.00007487212,0.00054371,0.00004388628,0.0001556285,0.000001720246,0.0002080498,0.00006446662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000460123,"about_ca_system_score_gemma":0.000006302384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000508244,"about_ca_topic_score_gemma":0.00002466548,"domain_scores_codex":[0.9994117,0.00001781295,0.0001497746,0.0001214148,0.0001600106,0.0001392868],"domain_scores_gemma":[0.9993876,0.00005871024,0.00001622611,0.0003661643,0.000062792,0.0001084977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009668905,0.0005827968,0.0004767808,0.0000819448,0.0006564282,0.00002581664,0.001101713,0.5038763,0.002527183,0.008038565,0.003785939,0.4787499],"study_design_scores_gemma":[0.001925037,0.0005718522,0.0006129504,0.00008446509,0.0004239056,0.0001021788,0.0005517221,0.4263551,0.1319207,0.3785996,0.0569713,0.001881242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004258754,0.00006685047,0.9936556,0.000266729,0.0001045562,0.00007354756,0.000004224575,0.0008494782,0.0007203095],"genre_scores_gemma":[0.9613348,0.0001769824,0.03820158,0.0001761134,0.00001609758,0.00003330713,0.000008715861,0.00002680045,0.0000256249],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.957076,"threshold_uncertainty_score":0.4603077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02448748680159069,"score_gpt":0.2642505096223811,"score_spread":0.2397630228207904,"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."}}