{"id":"W1677190615","doi":"10.1118/1.4925279","title":"MO‐AB‐BRA‐09: Temporally Realistic Manipulation a 4D Biomechanical Lung Phantom for Evaluation of Simultaneous Registration and Segmentation","year":2015,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Imaging phantom; Ground truth; Segmentation; Computer science; Bellows; Contouring; Breathing; Computer vision; Nuclear medicine; Biomedical engineering; Artificial intelligence; Simulation; Medicine; Materials science; Computer graphics (images)","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":[0.001108351,0.0004702864,0.00028651,0.0005664728,0.0001919912,0.0007172153,0.0006945086,0.0007875129,0.003646846],"category_scores_gemma":[0.001742002,0.0004466295,0.0003602353,0.0003502658,0.000358721,0.0003442682,0.0005667098,0.0005057036,0.0008225866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004059833,"about_ca_system_score_gemma":0.0007873643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001250595,"about_ca_topic_score_gemma":0.001493121,"domain_scores_codex":[0.9996766,0.00007686107,0.00002418045,0.00005258337,0.0001459012,0.00002392309],"domain_scores_gemma":[0.9993629,0.0002532417,0.0001004963,0.0001458154,0.00008628982,0.00005122473],"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":[0.0008203047,0.0002843635,0.002844077,0.0004780238,0.00008627028,0.0003506657,0.000228851,0.07267407,0.8747439,0.002085309,0.003796618,0.04160759],"study_design_scores_gemma":[0.0002119239,0.001776352,0.01822003,0.0001122278,0.0001055811,0.003135704,0.0001052801,0.3314588,0.6002559,0.001094989,0.04335083,0.0001723628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3749272,0.0007528361,0.6044224,0.0006579636,0.0001554165,0.0006854709,0.004234988,0.007028616,0.007135132],"genre_scores_gemma":[0.5814987,0.00044164,0.4051839,0.0002284086,0.00003101976,0.001174439,0.004499176,0.001677403,0.005265282],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003646846,"threshold_uncertainty_score":0.01219994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05467691116677252,"score_gpt":0.3820283296696194,"score_spread":0.3273514185028468,"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."}}