{"id":"W2078716434","doi":"10.1177/1077546307074225","title":"Adaptive Modeling of Laser Powder Deposition Process for Control and Monitoring Application","year":2007,"lang":"en","type":"article","venue":"Journal of Vibration and Control","topic":"Control Systems and Identification","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Process (computing); Deposition (geology); Laser power scaling; Laser; Process control; Power (physics); Control theory (sociology); Computer science; Function (biology); Adaptive control; Materials science; Control (management); Optics; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003810741,0.00006501097,0.0001684033,0.00009024317,0.00004212823,0.0000286938,0.00002638098,0.0000499798,3.580529e-7],"category_scores_gemma":[0.0000165652,0.00005924217,0.00003591303,0.00004214011,0.000007645845,0.0003031975,0.000001117566,0.00005384386,1.127457e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001916547,"about_ca_system_score_gemma":0.000009707786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004669217,"about_ca_topic_score_gemma":0.000006398911,"domain_scores_codex":[0.9993414,0.00001126529,0.000409057,0.00005848523,0.0001048886,0.00007486921],"domain_scores_gemma":[0.9993946,0.00005700429,0.0001849936,0.00003935626,0.0002782383,0.00004579522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001030825,0.00005481146,0.002816968,0.0002735222,0.0002320392,8.863688e-7,0.0007649344,0.2184769,0.7291733,0.0005180825,0.00001070018,0.046647],"study_design_scores_gemma":[0.002684875,0.00009926729,0.00302668,0.00006458032,0.00007673902,0.00001109482,0.0003528117,0.9822841,0.01102455,0.0002972881,0.00001293089,0.00006503065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2758402,0.0006235997,0.7231324,0.00004809536,0.00008611289,0.0002362401,0.000003402249,0.000008401025,0.00002155178],"genre_scores_gemma":[0.9993574,0.00002862162,0.0003278701,0.0000132354,0.0002448353,0.00001525059,0.000001233025,0.000008885836,0.000002643714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7638072,"threshold_uncertainty_score":0.2415826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009328210393815095,"score_gpt":0.2356567733409471,"score_spread":0.226328562947132,"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."}}