{"id":"W2951424830","doi":"10.48550/arxiv.1810.01285","title":"Area-Preserving Geometric Hermite Interpolation","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Parametrization (atmospheric modeling); Mathematics; Monotone cubic interpolation; Interpolation (computer graphics); Hermite interpolation; Curvature; Cubic Hermite spline; Hermite polynomials; Applied mathematics; Bézier curve; Mathematical analysis; Bicubic interpolation; Geometry; Linear interpolation; Computer science; Image (mathematics); Physics; Polynomial","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009958384,0.0005617319,0.000620161,0.0009556058,0.0005310815,0.0009907453,0.001046997,0.0007357621,0.00258769],"category_scores_gemma":[0.004732457,0.0003437366,0.000701305,0.0008040511,0.001600376,0.001602694,0.001803179,0.001779796,0.0007552077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007674693,"about_ca_system_score_gemma":0.0006229634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001265538,"about_ca_topic_score_gemma":0.0009445826,"domain_scores_codex":[0.9991659,0.0001258995,0.00002599732,0.0001233965,0.0004684615,0.00009043823],"domain_scores_gemma":[0.9990817,0.0002796756,0.0001130618,0.0003145319,0.0001680176,0.00004292102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001026705,0.00003703648,0.0006784016,0.0001313328,0.0000182075,0.0001046892,0.0002150818,0.2936748,0.01852651,0.5975959,0.001045245,0.08787008],"study_design_scores_gemma":[0.00001399732,0.0001353511,0.0003136721,0.00002476261,0.00001077413,0.000174085,0.00004252385,0.8251843,0.01182518,0.1496455,0.01259903,0.00003084782],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02004731,0.0001189229,0.9730262,0.00007706642,0.00003522222,0.00002210444,0.00004410729,0.0002248409,0.006404147],"genre_scores_gemma":[0.583231,0.0004586276,0.4076767,0.0001061848,0.00008637778,0.00006742607,0.000159084,0.0002882815,0.007926363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00258769,"threshold_uncertainty_score":0.008656621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05235438830362669,"score_gpt":0.189363839182005,"score_spread":0.1370094508783783,"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."}}