{"id":"W1972249942","doi":"10.1117/12.842409","title":"Coaxial real-time metrology and gas assisted laser micromachining: process development, stochastic behavior, and feedback control","year":2010,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Research and Innovation Foundation; Cancer Care Ontario","keywords":"Surface micromachining; Coaxial; Microsecond; Materials science; Laser; Metrology; Machining; Laser beam machining; Computer science; Optics; Coherence (philosophical gambling strategy); Laser cutting; Optical coherence tomography; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005476753,0.000416098,0.0005423778,0.0001379971,0.0001133632,0.0001856463,0.0005854625,0.0003283728,0.00001372418],"category_scores_gemma":[0.0003125811,0.0003677748,0.0001644009,0.0001884134,0.000359968,0.0004834322,0.000132179,0.0004504597,0.000001230749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007241709,"about_ca_system_score_gemma":0.00003707668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007400212,"about_ca_topic_score_gemma":5.2361e-7,"domain_scores_codex":[0.9980816,2.898779e-8,0.000670167,0.0004103549,0.0003936816,0.000444216],"domain_scores_gemma":[0.9985948,0.0001290354,0.0002510737,0.00005880076,0.0007956208,0.0001706723],"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":[0.0001063844,0.00007648258,0.0005542457,0.0006191459,0.0002959255,2.228308e-7,0.0002295471,0.00003972366,0.9871273,0.009781313,0.0004791273,0.0006905564],"study_design_scores_gemma":[0.005104928,0.0005947321,0.01237109,0.0005991095,0.0007896433,0.0002478293,0.0005428399,0.07639696,0.8983107,0.002469947,0.001008813,0.001563419],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977555,0.00003807342,0.00007231217,0.0003521816,0.0002315614,0.0005980449,0.00005034525,0.0003874444,0.0005145525],"genre_scores_gemma":[0.9327855,0.0000277954,0.06651819,0.00003280245,0.0002271603,0.0002571298,0.00001145132,0.0001000576,0.00003986947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08881664,"threshold_uncertainty_score":0.9998774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007717989841746174,"score_gpt":0.2271858335762985,"score_spread":0.2194678437345524,"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."}}