{"id":"W3084944599","doi":"10.1039/d0bm01046d","title":"Iodinated polymer nanoparticles as contrast agent for spectral photon counting computed tomography","year":2020,"lang":"en","type":"article","venue":"Biomaterials Science","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"Horizon 2020 Framework Programme","keywords":"Computed tomography; Contrast (vision); Nanoparticle; Polymer; Photon counting; Tomography; Materials science; Single-photon emission computed tomography; Chemistry; Photon; Nuclear medicine; Radiology; Physics; Nuclear magnetic resonance; Optics; Nanotechnology; Medicine","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":[0.0001982938,0.0001533677,0.0001836317,0.00007521397,0.0002174824,0.0002179615,0.0002745345,0.00002683712,0.00004456524],"category_scores_gemma":[0.0000385596,0.0001472275,0.00004569619,0.0005693344,0.0002258876,0.0003559498,0.00003954753,0.00001904864,0.00003250177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000304872,"about_ca_system_score_gemma":0.00002865011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001120273,"about_ca_topic_score_gemma":6.91143e-7,"domain_scores_codex":[0.9987954,0.00001012548,0.0002430278,0.0002803269,0.00019094,0.0004802076],"domain_scores_gemma":[0.9996268,0.00002537208,0.00004728741,0.0001115089,0.00005211821,0.0001369136],"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":[0.00002280789,0.000009539988,0.0001044081,0.00004413984,0.000007630902,0.000004368269,0.000229515,0.0003041818,0.9984002,0.0003653964,0.00005587604,0.000451947],"study_design_scores_gemma":[0.0003456388,0.00005167182,0.0006143718,0.0000273447,0.000008945986,0.000006211447,0.00008891031,0.02312296,0.9748968,0.00008511518,0.0005559185,0.0001961492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926396,0.0002754397,0.005214164,0.000151526,0.000735706,0.0002680523,0.00003657234,0.0005197646,0.0001591648],"genre_scores_gemma":[0.9973559,0.000004900675,0.002174489,0.0002955458,0.0001210015,0.0000205171,0.00000552343,0.00001886871,0.000003190924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02350343,"threshold_uncertainty_score":0.6003762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0145050771397561,"score_gpt":0.2353204675104083,"score_spread":0.2208153903706522,"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."}}