{"id":"W2049104356","doi":"10.1118/1.4814282","title":"SU‐E‐J‐70: Intra and Intermodality Validation of Registration Algorithms On a Deformable Phantom","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôtel-Dieu de Québec","funders":"","keywords":"Imaging phantom; Image registration; Metric (unit); Computer science; Deformation (meteorology); Artificial intelligence; Computer vision; Medical imaging; Translation (biology); Algorithm; Mutual information; Nuclear medicine; Mathematics; Image (mathematics); Medicine; Physics","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":[0.004881167,0.0006661952,0.0004919819,0.0009958142,0.0003302538,0.0009554274,0.00096974,0.0008604979,0.002529461],"category_scores_gemma":[0.007898498,0.0004393306,0.0004752915,0.0006299473,0.0006374479,0.0004993161,0.0008284797,0.0004832489,0.000815251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004054742,"about_ca_system_score_gemma":0.0006055064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001124185,"about_ca_topic_score_gemma":0.0008006255,"domain_scores_codex":[0.9980096,0.0006551322,0.000156486,0.0003508376,0.0007161245,0.0001119216],"domain_scores_gemma":[0.9965658,0.00155206,0.0003278935,0.0009061506,0.0005553946,0.00009280299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003351509,0.000806772,0.008881244,0.000604527,0.0002753844,0.0003223023,0.0006483677,0.06386064,0.7534102,0.002477775,0.002457836,0.1629035],"study_design_scores_gemma":[0.0001340137,0.002106345,0.01959499,0.00004306576,0.0001524528,0.001390473,0.0001048079,0.2247588,0.7446663,0.0006863697,0.006223823,0.0001385907],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6270663,0.0008194728,0.360084,0.0001363754,0.00009984563,0.000454169,0.0007617655,0.005836188,0.004741919],"genre_scores_gemma":[0.8020153,0.0001999034,0.1911563,0.00008608552,0.00001513934,0.0003996123,0.001850818,0.001423169,0.002853661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004881167,"threshold_uncertainty_score":0.02581441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212353196291362,"score_gpt":0.2420372499539657,"score_spread":0.2299137179910521,"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."}}