{"id":"W2292351303","doi":"10.1016/j.brachy.2011.02.113","title":"The Impact of Metal Artifact Correction on Post-implant Dose Distributions in Permanent Seed Implants","year":2011,"lang":"en","type":"article","venue":"Brachytherapy","topic":"Dental Implant Techniques and Outcomes","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal General Hospital; Université Laval; Centre hospitalier de l'Université Laval; Centre hospitalier universitaire de Québec","funders":"","keywords":"Medicine; Artifact (error); Nuclear medicine; Prostate; Voxel; Brachytherapy; Prostate brachytherapy; Hounsfield scale; Dosimetry; Absorbed dose; Biomedical engineering; Radiology; Artificial intelligence; Computed tomography; Radiation therapy; Computer science","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":[0.000219966,0.0001973262,0.000256012,0.000100623,0.0001349898,0.000036028,0.0002160278,0.00009501246,0.0001872464],"category_scores_gemma":[0.00003218172,0.0001216128,0.0002325052,0.0002031819,0.00005941348,0.0001335067,0.0000314687,0.0002145894,0.0001505349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000126083,"about_ca_system_score_gemma":0.00004248251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003447722,"about_ca_topic_score_gemma":0.001176267,"domain_scores_codex":[0.9987875,0.00009612276,0.0003861876,0.0002016467,0.000197156,0.000331336],"domain_scores_gemma":[0.9992166,0.0001359232,0.0001792968,0.0003403297,0.00005869057,0.00006915772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008777416,0.00329283,0.6754884,0.00003524212,0.0008765865,0.002361601,0.002684364,0.00003451751,0.1529697,0.0049019,0.01856416,0.1300134],"study_design_scores_gemma":[0.0006100941,0.0006196886,0.9709152,0.00002518531,0.00001235635,0.002511677,0.0001025552,0.00007044896,0.02440166,0.0003229543,0.0002582691,0.0001499065],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965123,0.00007417867,0.00005868915,0.00002130935,0.001115672,0.0003485034,0.0004878904,0.00008855538,0.001292928],"genre_scores_gemma":[0.9991142,0.00009425564,0.00002120321,0.00004255411,0.00003581442,0.00002862725,0.0001693651,0.00001917902,0.0004747757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2954269,"threshold_uncertainty_score":0.5211948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03347008095954566,"score_gpt":0.3256838162320433,"score_spread":0.2922137352724976,"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."}}