{"id":"W3011520136","doi":"","title":"Thermal modeling of DED repair process for slender panels by a 2D semi-analytic approach","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Equiaxed crystals; Thermal; Dwell time; Materials science; Annealing (glass); Process (computing); Work (physics); Microstructure; Simulated annealing; Mechanical engineering; Component (thermodynamics); Layer (electronics); Computer science; Mechanics; Composite material; Thermodynamics; Algorithm; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001376867,0.00034627,0.0005291887,0.00008115298,0.0001146178,0.0001232845,0.0007089348,0.0002406616,0.00006061719],"category_scores_gemma":[0.0004608395,0.000354009,0.000234285,0.0001409943,0.00007394572,0.00009478501,0.0003363846,0.000339434,0.000003385056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000050839,"about_ca_system_score_gemma":0.0001094658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009149001,"about_ca_topic_score_gemma":0.000008454455,"domain_scores_codex":[0.9978041,0.0005353575,0.0005459308,0.0005667012,0.0002588627,0.0002890624],"domain_scores_gemma":[0.9975126,0.0003972649,0.0002530174,0.0008195694,0.0009050057,0.0001125473],"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":[0.00008348628,0.0005650476,0.00008387689,0.01786965,0.001123247,0.000002479163,0.02504047,0.9148334,0.02668846,0.003441011,0.002442146,0.007826714],"study_design_scores_gemma":[0.0002330325,3.392043e-7,0.00002293652,0.0005676454,0.00009565034,0.000001019837,0.000111856,0.7925511,0.2037769,0.001794852,0.0005189721,0.0003257278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1261108,0.001011079,0.8592609,0.0004673954,0.0001234526,0.0006888545,0.0005177845,0.0006587669,0.01116098],"genre_scores_gemma":[0.9775355,0.0001595871,0.02066477,0.00002416202,0.00003425522,0.0002063837,0.0009166604,0.00008864558,0.000370033],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8514247,"threshold_uncertainty_score":0.9998912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03131647565719706,"score_gpt":0.2352996257684629,"score_spread":0.2039831501112658,"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."}}