{"id":"W4230562960","doi":"10.1016/j.cocis.2015.10.001","title":"Rheo-XPCS","year":2015,"lang":"en","type":"article","venue":"Current Opinion in Colloid & Interface Science","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Argonne National Laboratory; Basic Energy Sciences; Natural Sciences and Engineering Research Council of Canada; Research Triangle Institute; U.S. Department of Energy; National Science Foundation","keywords":"Rheology; Materials science; Deformation (meteorology); Shear (geology); Shear flow; Mechanics; Composite material; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006438181,0.0001469464,0.0001772646,0.0001821712,0.00009630118,0.00003543812,0.0005846688,0.00005084816,0.00002636015],"category_scores_gemma":[0.0006879286,0.0001371666,0.00003460727,0.0008229234,0.000549369,0.0002773665,0.00036955,0.0003057361,0.0001685643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002626862,"about_ca_system_score_gemma":0.0001561211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001395713,"about_ca_topic_score_gemma":0.000004115719,"domain_scores_codex":[0.9985741,0.00001983485,0.0002688434,0.0003887787,0.0003311484,0.0004172818],"domain_scores_gemma":[0.9993276,0.00006699294,0.00005127794,0.0002498711,0.0001455765,0.0001586968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000298514,0.0009125379,0.06048756,0.0004175526,0.00004648223,0.000002431901,0.01168383,0.06420437,0.2238887,0.5918702,0.03275111,0.01343659],"study_design_scores_gemma":[0.001472299,0.0001578752,0.002181992,0.0005448035,0.000005020164,0.00001666905,0.00102513,0.9542263,0.0155082,0.002955795,0.02125314,0.0006527558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3507093,0.01976528,0.5417441,0.00171664,0.0634083,0.0008230182,0.00003091674,0.0005468595,0.02125555],"genre_scores_gemma":[0.9974188,0.0002198232,0.001335093,0.00001220009,0.0001209853,0.000029093,0.000001980743,0.000009285433,0.0008527667],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8900219,"threshold_uncertainty_score":0.5593491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06923644443299275,"score_gpt":0.3629578079937379,"score_spread":0.2937213635607452,"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."}}