{"id":"W2895946939","doi":"10.2351/1.5062981","title":"3D finite element modelling of laser-assisted maskless micro-deposition","year":2013,"lang":"en","type":"article","venue":"","topic":"Adhesion, Friction, and Surface Interactions","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materials science; Finite element method; Constitutive equation; Deposition (geology); Laser; Thermal conduction; Selective laser sintering; Cladding (metalworking); Composite material; Forming processes; Stress (linguistics); Optics; Sintering; Structural engineering; 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":[0.00003664703,0.00009987853,0.000109775,0.00007617982,0.00005931371,0.00002366612,0.00005457159,0.00005266509,0.0008767549],"category_scores_gemma":[0.000002471777,0.00009489704,0.00005389015,0.0001042116,0.000009154727,0.000214535,0.000008749289,0.0000781434,0.0001899643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004917828,"about_ca_system_score_gemma":0.000006037682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003166999,"about_ca_topic_score_gemma":0.00004089464,"domain_scores_codex":[0.9993924,0.00001250879,0.000262646,0.00009674005,0.00009433947,0.0001413677],"domain_scores_gemma":[0.9996439,0.00005218861,0.00002988698,0.0001376652,0.000090162,0.00004615048],"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":[0.000002912537,0.00005048494,0.0004401331,0.00004102604,0.00004102133,5.241495e-7,0.0002017528,0.9578019,0.03794986,0.00004868244,0.002144298,0.001277367],"study_design_scores_gemma":[0.0001350227,0.00001959478,0.0006669938,0.00003026791,0.00001550862,0.000002854359,0.000245834,0.8875204,0.1100035,0.00007356505,0.001164522,0.0001219052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.466572,0.00004392334,0.5252958,0.00003590312,0.0002325361,0.0001209989,0.000005825154,0.0001778037,0.00751519],"genre_scores_gemma":[0.9748517,0.0000979256,0.02351204,0.00001813717,0.00003185759,0.00002413978,0.00001945829,0.00001958815,0.001425136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5082797,"threshold_uncertainty_score":0.9599851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01847763540546083,"score_gpt":0.2067076262566937,"score_spread":0.1882299908512328,"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."}}