{"id":"W2511346770","doi":"10.1016/j.jmatprotec.2016.08.030","title":"On material flow in Friction Stir Welded Al alloys","year":2016,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Advanced Welding Techniques Analysis","field":"Engineering","cited_by":127,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Friction stir welding; Welding; Materials science; Finite element method; Material flow; Flow (mathematics); Optical microscope; Composite material; Metallurgy; Mechanics; Scanning electron microscope; Structural engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002743513,0.0003271152,0.0003890779,0.001104934,0.0005683107,0.001105931,0.0004354192,0.0004910665,0.004218199],"category_scores_gemma":[0.0008394883,0.0002173788,0.0003317015,0.0003648915,0.0008353378,0.0009783556,0.0003657193,0.0003093737,0.0002835963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008572588,"about_ca_system_score_gemma":0.0005222835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004610349,"about_ca_topic_score_gemma":0.002010953,"domain_scores_codex":[0.9998845,0.00002221862,0.000005385785,0.0000253352,0.00003708286,0.00002554172],"domain_scores_gemma":[0.9998337,0.00007345207,0.00002467517,0.00001063692,0.00004149935,0.00001602908],"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":[0.004022266,0.0007302526,0.008916697,0.0006841169,0.00008947076,0.001077569,0.0007709126,0.2856467,0.5412567,0.07379928,0.001538741,0.08146734],"study_design_scores_gemma":[0.0001050006,0.0004250735,0.009884816,0.00003421089,0.00003859286,0.000155519,0.0002457121,0.8635499,0.1139944,0.008175867,0.003336743,0.00005423617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930389,0.002632051,0.05225798,0.000368365,0.0001918312,0.0001145675,0.0001834899,0.000291317,0.01357129],"genre_scores_gemma":[0.993206,0.0005122854,0.001527241,0.00001900253,0.0000306438,0.000007587477,0.00006875,0.00002257387,0.00460588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004610349,"threshold_uncertainty_score":0.01411128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006845176369634043,"score_gpt":0.2406107255985347,"score_spread":0.2337655492289007,"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."}}