{"id":"W2153472386","doi":"10.1088/0031-9155/52/19/002","title":"Optimization of a retrospective technique for respiratory-gated high speed micro-CT of free-breathing rodents","year":2007,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Robarts Clinical Trials; Toronto Metropolitan University","funders":"","keywords":"Nuclear medicine; Projection (relational algebra); Breathing; Image quality; Voxel; Scanner; Flat panel detector; Image registration; Biomedical engineering; Residual; Computer science; Medicine; Physics; Computer vision; Detector; Artificial intelligence; Algorithm; Optics; Anatomy; 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":[0.0007351919,0.00009141789,0.0004075338,0.0001183057,0.0000201936,6.741261e-7,0.00008537444,0.00007228,0.000009323339],"category_scores_gemma":[0.0003769235,0.00006846422,0.00003023708,0.0002799009,0.0003316776,0.00001877944,0.00004008376,0.0001512305,6.598022e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003094552,"about_ca_system_score_gemma":0.00002730277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002174152,"about_ca_topic_score_gemma":0.000002909965,"domain_scores_codex":[0.9991897,0.00002124324,0.000383466,0.0001912583,0.00007591958,0.0001383771],"domain_scores_gemma":[0.9992258,0.0001400247,0.0001806732,0.0002259704,0.0001779518,0.00004960217],"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":[0.0001314929,0.0001783013,0.01885764,0.0001717574,0.00003095191,0.000003476548,0.0001454212,0.00000908968,0.9651533,0.01218227,0.0008636396,0.002272618],"study_design_scores_gemma":[0.00444325,0.001767552,0.006359726,0.0009197624,0.0001508917,0.0000265086,0.0001623922,0.001693728,0.9376302,0.04587704,0.0008033039,0.0001656167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3385619,0.0001522716,0.6579052,0.001731766,0.00004600174,0.001069447,0.00002681432,0.00003716062,0.0004694353],"genre_scores_gemma":[0.9225163,0.00008591358,0.07673811,0.000403422,0.000151609,0.00002056006,0.00006324828,0.00001064956,0.0000101761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5839544,"threshold_uncertainty_score":0.279189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037413443560517,"score_gpt":0.4070357615104251,"score_spread":0.3032944171543734,"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."}}