{"id":"W3023761765","doi":"10.20382/jocg.v11i1a1","title":"On optimal polyline simplification using the Hausdorff and Fréchet distance","year":2018,"lang":"en","type":"article","venue":"Journal of Computational Geometry (Carleton University)","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Hausdorff distance; Subsequence; Combinatorics; Hausdorff space; Line segment; Line (geometry); Time complexity; Algorithm; Geometry; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009312194,0.0009097595,0.001620966,0.0013813,0.000987703,0.001617169,0.001477307,0.001077609,0.004811593],"category_scores_gemma":[0.006183542,0.0005348593,0.001282046,0.002402721,0.001612191,0.003600492,0.001834703,0.001529641,0.0009617328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519332,"about_ca_system_score_gemma":0.0009400912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003238303,"about_ca_topic_score_gemma":0.003683565,"domain_scores_codex":[0.9983202,0.0002671892,0.0001045817,0.0003683316,0.0007111609,0.0002285099],"domain_scores_gemma":[0.9972653,0.001540916,0.0002516728,0.0005494314,0.0002819906,0.0001106908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002331792,0.0001375805,0.00112561,0.0003578489,0.00007501951,0.0001933907,0.0002828794,0.6676913,0.01239023,0.09361497,0.004916952,0.218981],"study_design_scores_gemma":[0.00003562157,0.00008973249,0.0004850351,0.00003015809,0.00002219343,0.0001057347,0.0000843159,0.9311931,0.008694714,0.05399939,0.005234135,0.00002585294],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03623426,0.0005066727,0.9562024,0.0002534144,0.00004452236,0.00007270491,0.0001492067,0.0007815695,0.005755158],"genre_scores_gemma":[0.3015755,0.0007494363,0.6925468,0.0001193343,0.0000940387,0.0001204348,0.0008148456,0.0004867684,0.003492784],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004811593,"threshold_uncertainty_score":0.01609635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01587739429800557,"score_gpt":0.2400329222241248,"score_spread":0.2241555279261192,"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."}}