{"id":"W2896857333","doi":"10.3139/105.110360","title":"A Simple Model for Hardness and Residual Stress Profiles Prediction for Low-Alloy Nitrided Steel, Based on Nitriding-Induced Tempering Effects","year":2018,"lang":"en","type":"article","venue":"HTM Journal of Heat Treatment and Materials","topic":"Metal and Thin Film Mechanics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"Agence Nationale de la Recherche","keywords":"Nitriding; Tempering; Residual stress; Materials science; Metallurgy; Alloy; Alloy steel; Diffusion; Softening; Stress (linguistics); Hardness; Composite material; Layer (electronics); Thermodynamics","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":[0.0002351074,0.0005703801,0.0004342952,0.0002919479,0.0002474371,0.0003964247,0.000936132,0.0008994018,0.001152501],"category_scores_gemma":[0.0005862911,0.0003677568,0.0004845095,0.0001802528,0.0003747983,0.0004737897,0.0002326815,0.0004125564,0.0002594717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006658366,"about_ca_system_score_gemma":0.0004897654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008224651,"about_ca_topic_score_gemma":0.006097224,"domain_scores_codex":[0.9998939,0.00001516997,0.00000466388,0.00004045688,0.00003091464,0.00001496663],"domain_scores_gemma":[0.9998319,0.00006826198,0.00003152222,0.0000173535,0.0000417696,0.000009203466],"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":[0.00003017243,0.00003207291,0.0008526262,0.00003773839,0.00001446715,0.00008820718,0.00003217916,0.9731947,0.02164919,0.001044729,0.0001073473,0.002916695],"study_design_scores_gemma":[0.000001853027,0.000008097194,0.0002064232,7.236461e-7,0.000002187374,0.000004402188,9.879917e-7,0.9991463,0.0005067574,0.00008107955,0.00003918515,0.000001880936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4384636,0.0005364044,0.5505174,0.0002458876,0.00007203926,0.0001589055,0.0003794318,0.0008304373,0.008795823],"genre_scores_gemma":[0.9889953,0.0001454143,0.006866948,0.00001772821,0.000009428381,0.00007353647,0.00007819761,0.00003398533,0.003779405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008224651,"threshold_uncertainty_score":0.01635361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02524928099882252,"score_gpt":0.2462495056441689,"score_spread":0.2210002246453464,"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."}}