{"id":"W2914566827","doi":"10.3390/sym11020209","title":"Three Dimensional Point Cloud Compression and Decompression Using Polynomials of Degree One","year":2019,"lang":"en","type":"article","venue":"Symmetry","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Point cloud; Computer science; Lossy compression; Compression (physics); Segmentation; Algorithm; Degree (music); Data compression ratio; Point (geometry); Boundary (topology); Computer vision; Artificial intelligence; Image compression; Mathematics; Image (mathematics); Image processing; Geometry","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":[0.0002565491,0.000682105,0.0004424637,0.001052992,0.0003796112,0.0006138211,0.0006818901,0.0004366026,0.001896581],"category_scores_gemma":[0.001422179,0.0001579403,0.0004753588,0.001697478,0.000398694,0.0009583397,0.0007413236,0.0007121378,0.0007312797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003869619,"about_ca_system_score_gemma":0.0006097569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004329859,"about_ca_topic_score_gemma":0.003693184,"domain_scores_codex":[0.999598,0.00002206842,0.00002164476,0.00004477236,0.0002701991,0.00004321752],"domain_scores_gemma":[0.9995217,0.0001270362,0.00006148063,0.0001189193,0.000153148,0.00001770777],"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":[0.0005302803,0.000136483,0.001987795,0.0003160482,0.00005173501,0.0005670046,0.0003077443,0.1114203,0.1614836,0.008886382,0.006097601,0.7082151],"study_design_scores_gemma":[0.00004678128,0.0001686848,0.002393843,0.00002604888,0.00001647869,0.0009862949,0.0001277024,0.8568105,0.1281749,0.002985385,0.008222799,0.00004049976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1007662,0.00061319,0.8926719,0.0002698346,0.0001101308,0.0001301342,0.0004435734,0.002512147,0.002483038],"genre_scores_gemma":[0.4768892,0.0009349597,0.5169111,0.00008392254,0.00007633375,0.0001231348,0.001492303,0.0002546147,0.003234379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004329859,"threshold_uncertainty_score":0.008609295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695196416776333,"score_gpt":0.2344374219719125,"score_spread":0.2074854578041492,"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."}}