{"id":"W2950854424","doi":"10.1111/cgf.13878","title":"RodSteward: A Design‐to‐Assembly System for Fabrication using 3D‐Printed Joints and Precision‐Cut Rods","year":2019,"lang":"en","type":"preprint","venue":"Computer Graphics Forum","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Rod; Fabrication; Interface (matter); 3d printed; Computer science; Context (archaeology); Engineering drawing; Focus (optics); Visualization; Mechanical engineering; Engineering; Manufacturing engineering; Artificial intelligence; Optics; Physics; Parallel computing","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":[0.0007587745,0.001432696,0.0005931677,0.0006673482,0.0004565552,0.001094597,0.001382143,0.00106007,0.02388372],"category_scores_gemma":[0.001503354,0.001145043,0.001112573,0.0002502524,0.0006171641,0.0008916173,0.001936205,0.001238079,0.005103678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004175068,"about_ca_system_score_gemma":0.000718775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009444867,"about_ca_topic_score_gemma":0.001738046,"domain_scores_codex":[0.9992234,0.0001129673,0.00004659973,0.0001554117,0.0004051631,0.00005659292],"domain_scores_gemma":[0.9990118,0.0003849172,0.00009083075,0.0003291293,0.0001166754,0.00006655347],"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":[0.000625543,0.0002791862,0.001970825,0.0008502003,0.0001470836,0.001147242,0.001311647,0.06328024,0.5273482,0.0178245,0.03375284,0.3514625],"study_design_scores_gemma":[0.0003409036,0.0006999365,0.002436182,0.0001519365,0.00008137021,0.001461599,0.0001902852,0.2061039,0.4209299,0.005540223,0.3618029,0.0002609007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02371028,0.0002541167,0.8859565,0.00008263456,0.00009814801,0.0001986913,0.0005548423,0.07914943,0.009995404],"genre_scores_gemma":[0.1383515,0.0003563085,0.8233364,0.0001718761,0.00003431103,0.000426386,0.001738075,0.01238223,0.02320299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02388372,"threshold_uncertainty_score":0.07989901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03594553437422975,"score_gpt":0.255515134118417,"score_spread":0.2195695997441872,"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."}}