{"id":"W2972695518","doi":"10.2351/1.5061423","title":"Computer simulation of laser material removal: Measuring the depth of penetration in laser engraving","year":2008,"lang":"en","type":"article","venue":"","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Conestoga College","funders":"Ontario Centres of Excellence","keywords":"Engraving; Laser; Traverse; Materials science; Penetration depth; Machining; Optics; Transverse plane; Laser drilling; Laser power scaling; Laser beam machining; Mechanical engineering; Engineering; Laser beams; Geology; Composite material; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002515187,0.000343665,0.0004012612,0.0003860117,0.000268058,0.0005700958,0.0007421541,0.001111511,0.002144234],"category_scores_gemma":[0.0008739054,0.000339795,0.0005063523,0.0004690378,0.0004368838,0.00043067,0.0003935536,0.0005813794,0.0002450908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005073543,"about_ca_system_score_gemma":0.0007116439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005407341,"about_ca_topic_score_gemma":0.004219279,"domain_scores_codex":[0.9998518,0.00001937983,0.000008579334,0.00002143021,0.00007342188,0.00002529463],"domain_scores_gemma":[0.9995041,0.0003090051,0.00004706509,0.00003691417,0.00008380415,0.00001914499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003495956,0.00003193232,0.001025818,0.00008242136,0.00000843302,0.00006821635,0.00009191225,0.9823784,0.01047944,0.00139285,0.000170104,0.004235514],"study_design_scores_gemma":[0.000004233864,0.00001899128,0.0002529704,0.000004653255,0.000002897317,0.00001520139,0.0000133622,0.9955003,0.00351331,0.0002115569,0.0004574863,0.000005042897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6853105,0.000492367,0.2968624,0.0002953019,0.00007576701,0.0001662002,0.001003323,0.001608086,0.01418612],"genre_scores_gemma":[0.9362785,0.0002907743,0.05960103,0.0000340062,0.000004747822,0.0001998604,0.0003780622,0.00009045318,0.003122513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005407341,"threshold_uncertainty_score":0.01075172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02392654513886627,"score_gpt":0.2307518647567744,"score_spread":0.2068253196179081,"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."}}