{"id":"W4318261335","doi":"10.1016/b978-0-323-91911-1.00003-1","title":"3D-printed orthotics for pediatric lower limb deformities correction","year":2023,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Orthotics; Constraint (computer-aided design); Lower limb; Computer science; Physical medicine and rehabilitation; Medicine; Manufacturing engineering; Engineering; Mechanical engineering; Surgery","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":[0.0002065245,0.0008595397,0.0003040559,0.001014429,0.0001790077,0.0008408714,0.000615103,0.0007302461,0.04747155],"category_scores_gemma":[0.0003919375,0.0003105542,0.0006380514,0.000541018,0.0002816203,0.0004741544,0.0006661316,0.0008618339,0.01130302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001480673,"about_ca_system_score_gemma":0.0001835809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002822439,"about_ca_topic_score_gemma":0.001182204,"domain_scores_codex":[0.9997011,0.00002669139,0.00002100689,0.00001646179,0.0002239932,0.00001069431],"domain_scores_gemma":[0.9998773,0.00006855265,0.00001097496,0.00001399888,0.00002124736,0.000007932012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002852822,0.00006458855,0.0002811454,0.0007220387,0.00002100674,0.001020828,0.0001540035,0.003150705,0.01571431,0.006574451,0.0417211,0.9305474],"study_design_scores_gemma":[0.00002046581,0.0002337049,0.004240296,0.001679656,0.00005414122,0.02697266,0.0001196253,0.007317229,0.01550396,0.007079749,0.9367229,0.00005568592],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02474962,0.09020659,0.3904667,0.001434016,0.006977677,0.0002028314,0.001199365,0.003907234,0.4808559],"genre_scores_gemma":[0.1048296,0.06773935,0.1766089,0.001159145,0.001265523,0.0002497255,0.001219209,0.001591611,0.6453369],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04747155,"threshold_uncertainty_score":0.1588082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246074093977261,"score_gpt":0.21626459590973,"score_spread":0.2038038549699574,"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."}}