{"id":"W2077393517","doi":"10.1088/0031-9155/59/18/5611","title":"Corrigendum: A stoichiometric calibration method for dual energy computed tomography (2014 <i>Phys. Med. Biol.</i> 59 2059)","year":2014,"lang":"en","type":"erratum","venue":"Physics in Medicine and Biology","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; McGill University; Centre Hospitalier de l’Université de Montréal; Montreal General Hospital","funders":"Defense Advanced Research Projects Agency; U.S. Department of Agriculture","keywords":"Calibration; Dual energy; Computed tomography; Energy (signal processing); Dual (grammatical number); Stoichiometry; Physics; Nuclear medicine; Medical physics; Medicine; Radiology; Chemistry; Physical chemistry; Quantum mechanics; Philosophy","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":[0.001998845,0.002660495,0.001708853,0.004138548,0.002556743,0.003673488,0.003111298,0.004891537,0.09688366],"category_scores_gemma":[0.01853942,0.00127118,0.001705858,0.002893886,0.001686702,0.00227619,0.001974284,0.005223658,0.08120628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002781877,"about_ca_system_score_gemma":0.002379358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01367811,"about_ca_topic_score_gemma":0.02124526,"domain_scores_codex":[0.9972097,0.0003645547,0.0003258325,0.0003839135,0.001578504,0.0001374271],"domain_scores_gemma":[0.9919351,0.001440336,0.0003609248,0.0005862183,0.005404214,0.0002732739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000225925,0.000009589513,0.00007073794,0.0001832451,0.00001000879,0.0001462659,0.00001150253,0.0001226747,0.0002596346,0.001145146,0.9806262,0.01739247],"study_design_scores_gemma":[0.0000222307,0.00003999348,0.001142705,0.0002182915,0.00004625152,0.0004867147,0.00004236983,0.001022112,0.001886706,0.002055319,0.9929797,0.00005774603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0004664107,0.006515201,0.008279218,0.02809423,0.9303004,0.0001043725,0.001951737,0.001772232,0.02251617],"genre_scores_gemma":[0.01451456,0.0194176,0.02703817,0.04854045,0.1505777,0.0004656673,0.006265181,0.004018948,0.7291617],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.09688366,"threshold_uncertainty_score":0.3241081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0782842776112475,"score_gpt":0.3357831698007567,"score_spread":0.2574988921895092,"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."}}