{"id":"W6943779975","doi":"10.1594/essr2018/p-0057","title":"Multi-energy CT (MECT) in the acute MSK setting","year":2018,"lang":"en","type":"article","venue":"European Society of Radiology","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver General Hospital","funders":"","keywords":"Computed tomography; MEDLINE; Disease; Medical imaging","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":[0.0003841571,0.000115166,0.0001498688,0.00001789346,0.00007146583,0.000006337359,0.0002745689,0.00002098792,0.0000151066],"category_scores_gemma":[0.00001509997,0.00009333537,0.00009660557,0.0001311732,0.0002018815,0.00006482031,0.00004082695,0.0001926518,0.00002600791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002134975,"about_ca_system_score_gemma":0.000005245446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005151509,"about_ca_topic_score_gemma":0.000003428001,"domain_scores_codex":[0.999198,0.0001574821,0.0001907141,0.0001404146,0.00005274198,0.0002606699],"domain_scores_gemma":[0.9996291,0.00008505557,0.00003952673,0.0002072171,0.00001725985,0.00002177585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005307602,0.0002184247,0.01368476,0.0002429854,0.001177184,0.0004422404,0.08184328,0.0326043,0.3999301,0.002906617,0.337769,0.1291281],"study_design_scores_gemma":[0.004723374,0.0004600844,0.0550657,0.0001755511,0.0001329678,0.001837807,0.01059074,0.2798626,0.01706078,0.0006641803,0.6279488,0.001477449],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6961718,0.002938696,0.2625555,0.0009904065,0.001117772,0.000221888,0.00002883915,0.0005833521,0.03539181],"genre_scores_gemma":[0.9798983,0.0002674909,0.01846158,0.0008947068,0.0003178175,0.00000239996,0.000008999067,0.00003517877,0.0001135012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3828693,"threshold_uncertainty_score":0.3806106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00893158874661695,"score_gpt":0.2274043127681779,"score_spread":0.218472724021561,"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."}}