{"id":"W2088995202","doi":"10.1115/ipc2010-31033","title":"The Application of Quantitative X-Ray Diffraction (Rietveld Refinement) in Characterizing the Microstructure and Precipitates in Microalloyed Steels","year":2010,"lang":"en","type":"article","venue":"","topic":"Microstructure and Mechanical Properties of Steels","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Crystallite; Materials science; Microalloyed steel; Diffraction; Microstructure; Rietveld refinement; Carbide; Precipitation; Dissolution; X-ray crystallography; Metallurgy; Grain size; Analytical Chemistry (journal); Crystallography; Austenite; Chemical engineering; Chemistry; Chromatography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002926725,0.0005593678,0.0004609417,0.001008342,0.0003258618,0.0006149861,0.0008760222,0.0004547967,0.0005307602],"category_scores_gemma":[0.002972612,0.0007071799,0.0002544702,0.0005895914,0.0007155836,0.0006500868,0.0003293652,0.0005221006,0.000267652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004963533,"about_ca_system_score_gemma":0.0005021914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00221665,"about_ca_topic_score_gemma":0.005011613,"domain_scores_codex":[0.9986728,0.0003126895,0.0001272463,0.000236143,0.0005827937,0.00006828357],"domain_scores_gemma":[0.9981341,0.0007242245,0.0001848068,0.0002371012,0.0006811114,0.00003871826],"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":[0.00004176686,0.00001091269,0.0007356083,0.0001167594,0.000008925949,0.00004038751,0.00006438007,0.0005088492,0.9927376,0.0003237476,0.00003242672,0.005378698],"study_design_scores_gemma":[0.00001076249,0.0001571432,0.005634421,0.000009263192,0.00001940557,0.000285741,0.00008425425,0.008280069,0.9834496,0.0004104245,0.00164299,0.00001585915],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4445913,0.004260455,0.5456622,0.0002190059,0.00008886099,0.0004492723,0.0009614759,0.0008353834,0.002932019],"genre_scores_gemma":[0.5562457,0.001842248,0.4395736,0.00005273519,0.00001495392,0.0002331906,0.0004253357,0.0001396611,0.001472597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002926725,"threshold_uncertainty_score":0.01547819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006187631018526828,"score_gpt":0.215439420809338,"score_spread":0.2092517897908112,"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."}}