{"id":"W2027004994","doi":"10.1117/12.878696","title":"The sparse data extrapolation problem: strategies for soft-tissue correction for image-guided liver surgery","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Theoretical Astrophysics","keywords":"Computer science; Extrapolation; Imaging phantom; Computer vision; Image registration; Artificial intelligence; Context (archaeology); Interpolation (computer graphics); Residual; Point cloud; Image (mathematics); Algorithm; Optics; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001230749,0.0003146564,0.0004133584,0.00009966125,0.0001844065,0.0002155266,0.0009962122,0.0001673941,0.00001696457],"category_scores_gemma":[0.0008993397,0.0002390082,0.0005073032,0.0002735264,0.0002347507,0.001027776,0.000105222,0.0002380743,0.000002190936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009399025,"about_ca_system_score_gemma":0.00004926506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002787302,"about_ca_topic_score_gemma":8.638397e-7,"domain_scores_codex":[0.9978944,3.049344e-8,0.0007980353,0.0003892409,0.0004545162,0.0004637893],"domain_scores_gemma":[0.9975275,0.0005509418,0.0002928984,0.0001185059,0.001391208,0.0001189644],"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":[0.0001905847,0.000238592,0.0002745618,0.003246269,0.002099787,1.894561e-7,0.0009886441,0.001137727,0.4798376,0.2124984,0.2858209,0.01366679],"study_design_scores_gemma":[0.0007762271,0.0001346863,0.0002064478,0.0003703781,0.0004993373,0.00001734049,0.002064402,0.89892,0.07116129,0.00386848,0.02146843,0.0005129619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9630328,0.0004301685,0.02979794,0.001072079,0.001172156,0.001408914,0.0001730253,0.0002928724,0.002620012],"genre_scores_gemma":[0.4665307,0.0009920031,0.5271125,0.0001206158,0.001991753,0.001408263,0.0002297414,0.0002944609,0.001319992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8977823,"threshold_uncertainty_score":0.974647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04652494618689921,"score_gpt":0.255441442066465,"score_spread":0.2089164958795658,"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."}}