{"id":"W2043479890","doi":"10.1016/j.mechatronics.2006.05.002","title":"A mechatronics approach to laser powder deposition process","year":2006,"lang":"en","type":"article","venue":"Mechatronics","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":91,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mechatronics; PID controller; Detector; Process (computing); Laser; Controller (irrigation); Process control; Deposition (geology); Control system; Materials science; Control engineering; Engineering; Mechanical engineering; Computer science; Optics; Temperature control; Physics; Electrical engineering","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":[0.0002146688,0.0004260235,0.0004229804,0.0005616709,0.0008543016,0.001254167,0.0009882405,0.0008675746,0.006569087],"category_scores_gemma":[0.00030171,0.0003254535,0.00061251,0.0003188392,0.0009688317,0.0007806586,0.001198347,0.001104557,0.001498457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008680269,"about_ca_system_score_gemma":0.0007475477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001762228,"about_ca_topic_score_gemma":0.001595384,"domain_scores_codex":[0.9995143,0.00005393692,0.00001830912,0.0000539644,0.0003319282,0.00002747857],"domain_scores_gemma":[0.9999173,0.00002017465,0.00000846741,0.00001892939,0.00002970313,0.000005420703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006286686,0.00008357435,0.0003069784,0.0002433239,0.00003489028,0.0003802662,0.0002606507,0.05677016,0.1117846,0.7253468,0.003580709,0.1011452],"study_design_scores_gemma":[0.00006280502,0.0002823483,0.001540116,0.00009930485,0.00005561389,0.001004456,0.000155407,0.5115986,0.09979564,0.1966997,0.1886248,0.00008119586],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006323732,0.000690286,0.913294,0.001255606,0.0003697831,0.0001165653,0.00005616175,0.0003880027,0.07750588],"genre_scores_gemma":[0.3050256,0.002204514,0.5911385,0.000678736,0.0002161824,0.0003776905,0.0001592721,0.0002008942,0.09999869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006569087,"threshold_uncertainty_score":0.02197582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005106641758937432,"score_gpt":0.1902599741185373,"score_spread":0.1851533323595999,"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."}}