{"id":"W2100695923","doi":"10.1109/42.963814","title":"Organ motion detection in CT images using opposite rays in fan-beam projection systems","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Saint Mary's University","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Detector; Motion estimation; Motion compensation; Offset (computer science); Iterative reconstruction; Similarity (geometry); 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":[],"consensus_categories":[],"category_scores_codex":[0.0007732031,0.0002355196,0.0003630891,0.0007568103,0.0001576034,0.00005306942,0.0001275223,0.0001174009,0.0001413789],"category_scores_gemma":[0.00008282799,0.0002240625,0.00009923014,0.001224134,0.0001531376,0.0002755723,0.000003023435,0.001064143,0.00002303922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005147515,"about_ca_system_score_gemma":0.0001333849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003071286,"about_ca_topic_score_gemma":0.0001566715,"domain_scores_codex":[0.9975986,0.000124075,0.0006410788,0.0004988532,0.000697005,0.0004404294],"domain_scores_gemma":[0.9990876,0.0000991501,0.00009458313,0.000325666,0.00008445455,0.0003085831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002762283,0.002537377,0.01088807,0.0003835068,0.00005481449,0.001207477,0.0003651108,0.002078164,0.4010706,0.00002753874,0.0003146923,0.5807965],"study_design_scores_gemma":[0.003507663,0.0001261982,0.003989191,0.00213702,0.0001465603,0.003928196,0.0004407186,0.8031124,0.1808748,0.00009766037,0.001138234,0.0005012713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2807043,0.00005922768,0.7153774,0.002232668,0.0003696713,0.0006981385,0.00000305687,0.0002735272,0.0002819652],"genre_scores_gemma":[0.9970034,0.0002798084,0.001750274,0.0004284768,0.0001658411,0.0001985917,0.000008186593,0.00004661931,0.000118792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8010343,"threshold_uncertainty_score":0.9137003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02382590468218436,"score_gpt":0.3175419650966335,"score_spread":0.2937160604144491,"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."}}