{"id":"W1990905148","doi":"10.1007/s11661-013-2172-2","title":"A Deformation Mechanism Map for the 1.23Cr-1.2Mo-0.26V Rotor Steel and Its Verification Using Neural Networks","year":2014,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions A","topic":"High Temperature Alloys and Creep","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Life Prediction Technologies (Canada); University of Ottawa","funders":"","keywords":"Materials science; Creep; Deformation mechanism; Deformation (meteorology); Strain rate; Cavitation; Wedge (geometry); Artificial neural network; Grain Boundary Sliding; Structural engineering; Stress (linguistics); Composite material; Mechanics; Grain boundary; Computer science; Artificial intelligence; Engineering; Geometry; Physics; Mathematics","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":[0.0001007105,0.0003396455,0.0001526237,0.0005342013,0.0003187915,0.0002652697,0.0003400511,0.0006977072,0.006609235],"category_scores_gemma":[0.0003107542,0.0002104859,0.0003129755,0.0002334746,0.0002019828,0.0002973313,0.0001586162,0.0002436541,0.000607309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000320938,"about_ca_system_score_gemma":0.0005341662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01019262,"about_ca_topic_score_gemma":0.01026088,"domain_scores_codex":[0.9999701,0.000002074904,0.000001154517,0.000009426491,0.00001201626,0.000005171447],"domain_scores_gemma":[0.9999427,0.00001445296,0.000008042924,0.000007857127,0.00002282533,0.000004244901],"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":[0.0002009132,0.00009639793,0.003370974,0.0001333402,0.00003370384,0.0003853941,0.00008876021,0.8538381,0.03357834,0.0039705,0.002784796,0.1015187],"study_design_scores_gemma":[0.000006368677,0.00002257892,0.002486245,0.000005650045,0.000002716569,0.00004898096,0.00001491132,0.9940461,0.002390126,0.0005993789,0.0003698161,0.000007115974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7112876,0.0003466545,0.2620286,0.0005627209,0.0001478255,0.0001650253,0.001972535,0.003757414,0.0197317],"genre_scores_gemma":[0.9850079,0.00005006603,0.01263815,0.00001157894,0.000003531484,0.00002423779,0.0002567563,0.00003063042,0.00197717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01019262,"threshold_uncertainty_score":0.0221101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113356529553153,"score_gpt":0.1994984843645864,"score_spread":0.1881628314092711,"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."}}