{"id":"W2520291634","doi":"","title":"Variations in Grain Size and Viscosity Based on Vacancy Diffusion in Minerals, Seismic Tomography and Geodynamically Inferred Mantle Rheology","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"High-pressure geophysics and materials","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Mantle (geology); Grain size; Geology; Rheology; Viscosity; Arrhenius equation; Seismic tomography; Diffusion creep; Mineralogy; Geophysics; Thermodynamics; Materials science; Grain boundary; Microstructure; Physics; Chemistry; Activation energy; Composite material","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":[0.0002456928,0.0002306091,0.0001949583,0.001409858,0.000146068,0.0007148955,0.0003139775,0.0002618561,0.0004869516],"category_scores_gemma":[0.00195519,0.0002731133,0.0001887541,0.0007388513,0.0004035581,0.0009027321,0.0004070299,0.0002188559,0.00008624054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003497175,"about_ca_system_score_gemma":0.00009268547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002542729,"about_ca_topic_score_gemma":0.004427752,"domain_scores_codex":[0.9999158,0.00001204448,0.000006204287,0.00003043719,0.00002607878,0.000009331119],"domain_scores_gemma":[0.9995105,0.0002004072,0.0001767013,0.00004049969,0.0000387904,0.00003303222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005280901,0.00006390997,0.4146269,0.0001659212,0.0001558097,0.0003159963,0.000437904,0.0378022,0.5021239,0.002921723,0.0002789527,0.04057874],"study_design_scores_gemma":[0.00002480786,0.00006672722,0.7004607,0.00001940048,0.00006916322,0.0003453221,0.0001286148,0.2444823,0.05104477,0.002810344,0.0004857692,0.00006210971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916864,0.0001805204,0.007186557,0.00004063752,0.000003780311,0.000005897178,0.00018237,0.00007437353,0.0006393923],"genre_scores_gemma":[0.9977113,0.00005950252,0.002073809,0.000003900732,0.000002599498,0.000002661646,0.00008615124,0.0000110861,0.00004888959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002542729,"threshold_uncertainty_score":0.005055845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008875623031422187,"score_gpt":0.2144504214618332,"score_spread":0.205574798430411,"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."}}