{"id":"W4319005247","doi":"10.3390/surgeries4010008","title":"Utilizing Additive Manufacturing to Produce Organ Mimics and Imaging Phantoms","year":2023,"lang":"en","type":"article","venue":"Surgeries","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"Biotalent Canada; Canada Research Chairs","keywords":"Flexibility (engineering); Workflow; 3D printing; Computer science; Process (computing); Systems engineering; Field (mathematics); Manufacturing engineering; Process engineering; Engineering; Mechanical engineering; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001615157,0.0008021027,0.0003381378,0.001340218,0.000404125,0.001941206,0.0007151755,0.0008471652,0.002503463],"category_scores_gemma":[0.001863208,0.0006896395,0.0007442052,0.0005987193,0.0007726214,0.0009022244,0.00133755,0.0009059907,0.001669484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003540043,"about_ca_system_score_gemma":0.0005270329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002139137,"about_ca_topic_score_gemma":0.0004934916,"domain_scores_codex":[0.9990526,0.0001461133,0.00006277014,0.0001064995,0.0005649493,0.00006707558],"domain_scores_gemma":[0.9989579,0.0003850908,0.0001521063,0.0002853911,0.000158531,0.000061101],"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":[0.0001286029,0.0001267442,0.0006904102,0.001041949,0.00005686831,0.00137939,0.0005117831,0.0148526,0.8520118,0.02375466,0.002664935,0.1027804],"study_design_scores_gemma":[0.00002555317,0.0007388531,0.001012594,0.000195609,0.0001003984,0.003238219,0.0001186338,0.01646967,0.8392429,0.004845973,0.1339066,0.0001049254],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07539355,0.004422478,0.8753954,0.0005952358,0.0007831079,0.0006418172,0.0004407132,0.002487402,0.0398403],"genre_scores_gemma":[0.3059922,0.005355566,0.6761557,0.0005166093,0.0001161712,0.0005777956,0.0003937413,0.0004775748,0.01041459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002503463,"threshold_uncertainty_score":0.008541822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007053035608353032,"score_gpt":0.2149711922883652,"score_spread":0.2079181566800122,"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."}}