{"id":"W2988536782","doi":"10.1016/j.jnucmat.2019.151882","title":"A method for calculation of bias factor in anisotropic mediums, application to <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si1.svg\"><mml:mrow><mml:mi>α</mml:mi><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">−</mml:mo></mml:mrow></mml:math>zirconium","year":2019,"lang":"lv","type":"article","venue":"Journal of Nuclear Materials","topic":"Nuclear Materials and Properties","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electron backscatter diffraction; Anisotropy; Materials science; Equiaxed crystals; Cluster (spacecraft); Grain boundary; Condensed matter physics; Crystallite; Geometry; Physics; Mathematics; Composite material; Optics; Computer science; Metallurgy; Microstructure","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002527774,0.0004323493,0.0005311839,0.0003050522,0.0002558166,0.0008473788,0.0008916859,0.0008338438,0.01446778],"category_scores_gemma":[0.0006129597,0.0005441207,0.0005085692,0.0002886084,0.0002302662,0.0008802372,0.0005870153,0.0003084057,0.00145086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002874528,"about_ca_system_score_gemma":0.0003859329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001051152,"about_ca_topic_score_gemma":0.0001028857,"domain_scores_codex":[0.9951268,0.0004455106,0.001932423,0.0006692987,0.001015646,0.0008102983],"domain_scores_gemma":[0.9959993,0.0004190976,0.002249559,0.0007274971,0.0002544645,0.0003501133],"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":[0.00253876,0.0001652277,0.000007291885,0.001191864,0.0001997432,0.00004827737,0.001897795,0.0003474569,0.7135547,0.2763014,0.002761237,0.0009863127],"study_design_scores_gemma":[0.001429001,0.001961186,0.001066342,0.001142013,0.0003837029,0.000357315,0.0007010074,0.02174067,0.9618966,0.0002317618,0.008511518,0.0005788834],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941869,0.0002006684,0.0003481829,0.000578784,0.002464834,0.0001375932,0.0003979761,0.00005267869,0.001632337],"genre_scores_gemma":[0.98594,0.0003083849,0.01095121,0.000724875,0.001552146,0.0001279899,0.00006624656,0.0002756346,0.00005350998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2760696,"threshold_uncertainty_score":0.999701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02330853168907967,"score_gpt":0.2631464807670038,"score_spread":0.2398379490779241,"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."}}