{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001198591,0.001330885,0.001763444,0.001359985,0.0005476722,0.002225456,0.003079349,0.001748224,0.006158214],"category_scores_gemma":[0.004368923,0.0009940108,0.001429875,0.001511316,0.001605763,0.003503701,0.005196012,0.002805558,0.002389934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007317543,"about_ca_system_score_gemma":0.001144528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002145635,"about_ca_topic_score_gemma":0.002729552,"domain_scores_codex":[0.998552,0.000171471,0.0001081723,0.0002893293,0.0007459393,0.000133081],"domain_scores_gemma":[0.9978143,0.0004371298,0.0002032346,0.0009576358,0.0004698987,0.0001177618],"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":[0.0002963632,0.000164202,0.002360207,0.0002650421,0.0001309031,0.0002709049,0.0005023555,0.390905,0.04612957,0.07218385,0.005718876,0.4810728],"study_design_scores_gemma":[0.00002352408,0.00009445299,0.0003251732,0.00002818054,0.00002534127,0.0001691347,0.00006689141,0.9542468,0.01535147,0.02026207,0.009375218,0.00003179544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004931886,0.00007270308,0.9936596,0.0000365528,0.00002324703,0.00003481652,0.00003565066,0.0004773007,0.0007283077],"genre_scores_gemma":[0.2015344,0.0002439005,0.790796,0.000214951,0.00006996541,0.0002385545,0.0006144064,0.0007825196,0.005505248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006158214,"threshold_uncertainty_score":0.02060121,"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."}}