{"id":"W2132711335","doi":"10.1186/1687-5281-2014-25","title":"Efficient robust image interpolation and surface properties using polynomial texture mapping","year":2014,"lang":"en","type":"article","venue":"EURASIP Journal on Image and Video Processing","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Polynomial; Interpolation (computer graphics); Mathematics; Pattern recognition (psychology); Computer science; Curse of dimensionality; Robustness (evolution); Polynomial interpolation; Computer vision; Algorithm; Linear interpolation; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0007057337,0.0001927484,0.0001963807,0.0002411495,0.0006482574,0.002101293,0.0002464255,0.00005600609,0.000001922085],"category_scores_gemma":[0.0000654236,0.0001529921,0.00004308359,0.0002865939,0.00008926055,0.0007746589,0.0001880428,0.0002985462,8.260095e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000269233,"about_ca_system_score_gemma":0.00005145965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006261562,"about_ca_topic_score_gemma":4.912394e-7,"domain_scores_codex":[0.998728,0.0001263502,0.0003427536,0.0003264819,0.0002386281,0.0002378085],"domain_scores_gemma":[0.9992037,0.00004145228,0.0002677528,0.0001440818,0.0002170846,0.000125963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001393939,0.0003569378,0.005186804,0.0008401452,0.00007466323,0.00008717029,0.01672063,0.002591974,0.5154175,0.007032241,0.001184124,0.4503685],"study_design_scores_gemma":[0.0002855151,0.0001064035,0.001032919,0.0005949731,0.0000072189,0.0002845359,0.00007922672,0.9908659,0.005887124,0.0003093342,0.0003285585,0.0002183222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2992787,0.0003980625,0.6996548,0.000328207,0.00009700379,0.00006868717,2.655007e-7,0.00008106219,0.00009325232],"genre_scores_gemma":[0.9125171,0.00003715689,0.08687437,0.0003630384,0.0001776477,7.181408e-7,3.322821e-7,0.00001558603,0.00001410013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9882739,"threshold_uncertainty_score":0.9989346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02941314766857744,"score_gpt":0.27513876827529,"score_spread":0.2457256206067125,"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."}}