{"id":"W2100302985","doi":"10.1142/s021819591360011x","title":"ROBUST NONPARAMETRIC SIMPLIFICATION OF POLYGONAL CHAINS","year":2013,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Subsequence; Polygonal chain; Combinatorics; Cardinality (data modeling); Simple (philosophy); Nonparametric statistics; Sequence (biology); Mathematics; Monotonic function; Chain (unit); Piecewise; Piecewise linear function; Plane (geometry); Binary logarithm; Algorithm; Discrete mathematics; Computer science; Geometry; Bounded function; Regular polygon; Mathematical analysis; Statistics","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":[0.002276156,0.0008356129,0.001985057,0.002178882,0.000776216,0.001516712,0.002839148,0.00105915,0.002264704],"category_scores_gemma":[0.01384444,0.0009973039,0.001425632,0.002433624,0.001567933,0.00257835,0.002276208,0.002241676,0.0007654651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087671,"about_ca_system_score_gemma":0.001308651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003832525,"about_ca_topic_score_gemma":0.003904882,"domain_scores_codex":[0.9976649,0.000568117,0.0001248527,0.0004955899,0.0009671155,0.0001794109],"domain_scores_gemma":[0.993924,0.002886459,0.0008281675,0.001745172,0.0004443239,0.0001718431],"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":[0.0002081535,0.0000456727,0.002529981,0.000120906,0.00009046334,0.0001833883,0.0001778941,0.812744,0.009039699,0.02275794,0.0012005,0.1509013],"study_design_scores_gemma":[0.000005471035,0.00002559738,0.0002801979,0.000007455402,0.0000066609,0.00006092049,0.00001819008,0.9887158,0.001994919,0.007668818,0.001206327,0.000009589063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01191953,0.00007620451,0.9871826,0.00003679668,0.000008310908,0.00002099615,0.00007692687,0.0003203865,0.0003582254],"genre_scores_gemma":[0.311125,0.0003384537,0.6843989,0.00007787359,0.00007780434,0.0001860577,0.001297989,0.0003511182,0.00214681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003832525,"threshold_uncertainty_score":0.01203758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01943784998104875,"score_gpt":0.2681427390046353,"score_spread":0.2487048890235865,"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."}}