{"id":"W2072212482","doi":"10.1007/s00170-010-2886-x","title":"Contour generation for layered manufacturing with reduced part distortion","year":2010,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Distortion (music); Process (computing); Representation (politics); Layer (electronics); Point cloud; Point (geometry); Geometry; Set (abstract data type); Boundary (topology); Computer science; Boundary layer; Engineering drawing; Mechanical engineering; Engineering; Computer vision; Materials science; Mathematics; Composite material; Mathematical analysis","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":[0.0003009659,0.0007404305,0.0005313686,0.0004834254,0.0002047018,0.000702734,0.000812492,0.0008259621,0.004223089],"category_scores_gemma":[0.001115351,0.0005122774,0.0007111944,0.0006072547,0.0003072324,0.0006867167,0.0009862178,0.0008093232,0.0007305128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000331642,"about_ca_system_score_gemma":0.0003543203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005925727,"about_ca_topic_score_gemma":0.0008382601,"domain_scores_codex":[0.999764,0.00003821207,0.00001152678,0.00003345993,0.0001312291,0.0000215398],"domain_scores_gemma":[0.9995481,0.0001653025,0.00005015107,0.0001282733,0.00008557369,0.00002249394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004356992,0.00009384869,0.0006826684,0.0001756799,0.0000654681,0.00034907,0.0001566095,0.5332245,0.1793235,0.01904315,0.002325714,0.2641241],"study_design_scores_gemma":[0.00001730555,0.0000755131,0.0001876345,0.000008627581,0.00001444235,0.0001014134,0.000007991797,0.9704986,0.02453577,0.00307328,0.001462029,0.00001742327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01871658,0.00007359473,0.9783792,0.00003530505,0.00002821749,0.00002239571,0.00004651705,0.0006103264,0.002087768],"genre_scores_gemma":[0.3849037,0.00009880883,0.6117309,0.00005116167,0.00001848745,0.00005006242,0.0001783063,0.000289476,0.002679146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004223089,"threshold_uncertainty_score":0.01412761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008685394424591633,"score_gpt":0.2265932781768294,"score_spread":0.2179078837522378,"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."}}