{"id":"W2076244694","doi":"10.1118/1.3077923","title":"Adapting liver motion models using a navigator channel technique","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"National Cancer Institute; National Institutes of Health; Terry Fox Foundation","keywords":"Computer vision; Population; Artificial intelligence; Image registration; Motion (physics); Computer science; Voxel; Channel (broadcasting); Motion estimation; Medical imaging; Mathematics; Image (mathematics); Medicine","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":[0.0003724417,0.0004280787,0.0003690846,0.0003823628,0.0001827827,0.0003082464,0.0004206261,0.0005851558,0.0008312105],"category_scores_gemma":[0.00101878,0.0003922562,0.0007760656,0.0003524931,0.000210386,0.0003461539,0.000510345,0.000579633,0.0003079289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002748464,"about_ca_system_score_gemma":0.0007194143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003289324,"about_ca_topic_score_gemma":0.005043157,"domain_scores_codex":[0.9998036,0.00004449673,0.000009795976,0.00005264349,0.00006889041,0.00002057199],"domain_scores_gemma":[0.9998184,0.00007070124,0.00002657595,0.00003556452,0.0000382593,0.00001057992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009304411,0.00006149816,0.003985138,0.00003920254,0.00008930419,0.0001135809,0.0001427872,0.7252063,0.103713,0.002374964,0.0008544723,0.1633267],"study_design_scores_gemma":[0.00001413673,0.0001080939,0.00186883,0.00000331376,0.00002160627,0.0001090687,0.00001435262,0.9825183,0.01251548,0.0009185019,0.00187502,0.00003337991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04738402,0.00003700535,0.9509677,0.00004614939,0.00001609834,0.00004356297,0.00005717039,0.0009334279,0.0005148579],"genre_scores_gemma":[0.5382119,0.0001342629,0.4589144,0.00008964881,0.00002148315,0.000245474,0.0004299414,0.0002499477,0.001702916],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003289324,"threshold_uncertainty_score":0.006540358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0258178464745157,"score_gpt":0.2955386952421781,"score_spread":0.2697208487676624,"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."}}