{"id":"W2092104875","doi":"10.4028/www.scientific.net/ssp.172-174.221","title":"Martensite Fraction Determination Using Cooling Curve Analysis","year":2011,"lang":"en","type":"article","venue":"Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena","topic":"Microstructure and Mechanical Properties of Steels","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Martensite; Fraction (chemistry); Cooling curve; Materials science; Thermodynamics; Alloy; Work (physics); Mechanics; Metallurgy; Chemistry; Physics; Microstructure; Chromatography","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":[0.0003440713,0.000540845,0.0003905553,0.003608549,0.0005373245,0.000508535,0.0005514047,0.0003203868,0.003024345],"category_scores_gemma":[0.0008628889,0.0002582075,0.00028899,0.001166929,0.0002119411,0.0005872336,0.0002772028,0.0004009297,0.001117996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000509123,"about_ca_system_score_gemma":0.0004387029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004274126,"about_ca_topic_score_gemma":0.007456658,"domain_scores_codex":[0.9995752,0.00001530838,0.00001664394,0.00009228032,0.0002719563,0.00002858237],"domain_scores_gemma":[0.9993148,0.0001308116,0.00007120609,0.00005474382,0.0004035419,0.00002499218],"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":[0.0001031391,0.00002863286,0.007173259,0.000116935,0.00002341854,0.00005176786,0.000114053,0.003010548,0.9039074,0.0009372881,0.0003496449,0.08418392],"study_design_scores_gemma":[0.0000092465,0.00008326431,0.02186769,0.00001449104,0.00002552179,0.0001977487,0.00004598669,0.02971735,0.9377208,0.0005154193,0.009765423,0.0000371602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.604823,0.002383473,0.3742831,0.00007077889,0.00007235531,0.0002083469,0.00200173,0.002750455,0.01340678],"genre_scores_gemma":[0.8919886,0.0008374555,0.09964792,0.0000152295,0.00001941166,0.00007809953,0.001219035,0.0004555519,0.005738579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004274126,"threshold_uncertainty_score":0.01011741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06225678043088952,"score_gpt":0.2837209362447823,"score_spread":0.2214641558138928,"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."}}