{"id":"W1987114335","doi":"10.1016/j.commatsci.2010.05.027","title":"FEM–DEM modeling of thermal conductivity of porous pigmented coatings","year":2010,"lang":"en","type":"article","venue":"Computational Materials Science","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Coating; Materials science; Thermal conductivity; Composite material; Porosity; Volume fraction; Layer (electronics); Thermal; Thermodynamics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006089597,0.00009756823,0.0002448317,0.00008468948,0.0002221657,0.0001529087,0.0002699661,0.00002079149,0.002038843],"category_scores_gemma":[0.00009064379,0.00007727883,0.00003704101,0.00008374104,0.0009169017,0.0004185314,0.0000997692,0.00003893264,0.00001084231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001199452,"about_ca_system_score_gemma":0.00007991546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000597895,"about_ca_topic_score_gemma":0.00005615409,"domain_scores_codex":[0.9988318,0.00003258782,0.0004071134,0.0001971679,0.0003841719,0.0001471664],"domain_scores_gemma":[0.998916,0.00004719448,0.0002749807,0.0001233534,0.0006014528,0.00003702191],"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":[0.00001306917,0.00003820573,0.0000264728,0.00002947636,0.000005818338,3.727422e-7,0.002719954,0.008263348,0.9357305,0.05309465,0.000004959471,0.00007315113],"study_design_scores_gemma":[0.0004996434,0.0001220707,0.001761292,0.00007297261,0.00005464,0.000009076874,0.00201652,0.05790489,0.9217553,0.01535304,0.00007232283,0.0003782036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977982,0.000006385072,0.0001559472,0.00006038129,0.0007113889,0.00009507877,0.00009597483,0.00002422978,0.001052414],"genre_scores_gemma":[0.9982196,4.104936e-7,0.001543738,0.00002424091,0.0001390703,0.000004033481,0.00001800013,0.000006450397,0.0000444295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04964154,"threshold_uncertainty_score":0.9988734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04783716515256689,"score_gpt":0.259433680921931,"score_spread":0.2115965157693641,"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."}}