{"id":"W776618452","doi":"10.1007/s00170-015-7423-5","title":"Real-time control of microstructure in laser additive manufacturing","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":137,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microstructure; Controller (irrigation); Materials science; Process control; Process (computing); PID controller; Deposition (geology); Temperature control; Thermal; Laser; Control theory (sociology); Mechanical engineering; Computer science; Composite material; Optics; Engineering; Control (management)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002168261,0.0001338067,0.0001635154,0.0001658897,0.0001323719,0.0003592866,0.0003600756,0.000204814,0.0007738158],"category_scores_gemma":[0.0004900147,0.0001116959,0.00006756222,0.0001860921,0.0002194268,0.0002655056,0.0001882765,0.0001796204,0.0001130467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966571,"about_ca_system_score_gemma":0.0001958574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005799115,"about_ca_topic_score_gemma":0.00153829,"domain_scores_codex":[0.9998312,0.0000198233,0.000005625608,0.00002811667,0.0001025676,0.00001259694],"domain_scores_gemma":[0.9997724,0.00009757858,0.00005113769,0.00001819103,0.00004363834,0.00001711419],"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":[0.0006053893,0.00008179025,0.0007451971,0.00008166196,0.000008719193,0.00005645294,0.00007699025,0.01410171,0.8869684,0.001358968,0.0004098451,0.09550478],"study_design_scores_gemma":[0.00007241695,0.0005881674,0.008961471,0.000008717521,0.00001437908,0.0001626219,0.00004348236,0.6432667,0.3422633,0.001341034,0.003237132,0.0000406019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7093812,0.001236284,0.2829844,0.000260554,0.0002861119,0.00004181383,0.00009550711,0.001062009,0.004652199],"genre_scores_gemma":[0.9809899,0.0001069508,0.01810594,0.00002304302,0.00001602546,0.000009559462,0.00001275567,0.00001655081,0.0007192271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007738158,"threshold_uncertainty_score":0.002588689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00553022598799262,"score_gpt":0.2217298798263756,"score_spread":0.2161996538383829,"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."}}