{"id":"W4386167685","doi":"10.1007/s10845-023-02194-1","title":"Intermittent adaptive trajectory planning for geometric defect correction in large-scale robotic laser directed energy deposition based additive manufacturing","year":2023,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deposition (geology); Trajectory; Kinematics; Laser scanning; Scanner; Computer science; Scale (ratio); Materials science; Mechanical engineering; Simulation; Laser; Artificial intelligence; Engineering; Optics; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005132951,0.000419304,0.000605025,0.001786353,0.0001408289,0.0001083241,0.0002457665,0.0001720063,0.000118347],"category_scores_gemma":[0.0001011678,0.0003949947,0.0003660235,0.0003509405,0.00002732647,0.0003813758,0.00004966588,0.0004201622,0.00001472146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004884912,"about_ca_system_score_gemma":0.00003834951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002370546,"about_ca_topic_score_gemma":0.00007156436,"domain_scores_codex":[0.9977192,0.00009689898,0.0008867597,0.0003090495,0.0003466508,0.0006414442],"domain_scores_gemma":[0.9984546,0.0007738821,0.0003577673,0.0001493882,0.0001138665,0.0001505213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004094323,0.00008670769,0.0001245737,0.0002668223,0.0002096619,0.0001505509,0.0005562501,0.9608855,0.001149318,0.000001391772,0.001582463,0.03457738],"study_design_scores_gemma":[0.000682125,0.0002569221,0.01262734,0.0007809924,0.00008117186,0.00004996308,0.0006409602,0.06332673,0.919934,0.00009577174,0.00111642,0.000407549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6478175,0.0002633139,0.3485551,0.00001297325,0.002583099,0.0002433096,0.00004919546,0.0003057,0.0001697666],"genre_scores_gemma":[0.9979323,0.0002152538,0.001021678,0.00004562975,0.0004533571,0.0000628208,0.00008816704,0.00009879848,0.00008195481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9187847,"threshold_uncertainty_score":0.9998502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735190074965216,"score_gpt":0.234928188842124,"score_spread":0.2175762880924719,"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."}}