{"id":"W2089696979","doi":"10.1179/174892309x12519750237636","title":"Improved approach for predicting weld creep strength factors of ferritic steels","year":2009,"lang":"en","type":"article","venue":"Energy Materials","topic":"High Temperature Alloys and Creep","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Environment and Climate Change Canada; Academy of Finland","keywords":"Creep; Extrapolation; Welding; Materials science; Metallurgy; Stress (linguistics); Structural engineering; Engineering; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001143272,0.0001948756,0.0003465167,0.00005852899,0.00004712772,0.00005246541,0.0001530929,0.0001420158,0.00007416194],"category_scores_gemma":[0.00002770616,0.0001695101,0.00006817411,0.00006761588,0.00001419519,0.0001017061,0.00001217565,0.00004387071,3.244308e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002032318,"about_ca_system_score_gemma":0.000009589563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004540982,"about_ca_topic_score_gemma":0.000004943375,"domain_scores_codex":[0.9990753,0.00002259249,0.0003504271,0.0001731603,0.00009741408,0.0002811215],"domain_scores_gemma":[0.9995966,0.00004131981,0.00005150534,0.0002110148,0.00003497784,0.0000645988],"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":[0.00002207777,0.00004575466,0.00001976729,0.0001124727,0.00006078961,5.970234e-7,0.0001475796,0.003940118,0.9900424,0.004751239,0.0003134007,0.0005438307],"study_design_scores_gemma":[0.000396776,0.0001660893,0.0004976743,0.00002763362,0.00003055642,0.000001372252,0.00008612376,0.004458718,0.9926122,0.0001347733,0.001368207,0.0002198106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856729,0.0001780689,0.01038698,0.00001181664,0.0004907361,0.000169618,0.000178368,0.0002900194,0.002621521],"genre_scores_gemma":[0.9966324,0.00001792422,0.002601774,0.00002343865,0.0002868148,0.00003170617,0.0001658071,0.0000368823,0.0002032668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01095951,"threshold_uncertainty_score":0.6912419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007095542385539789,"score_gpt":0.1943526227533092,"score_spread":0.1872570803677694,"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."}}