{"id":"W3165242308","doi":"10.11159/iccste21.130","title":"Aggregate Moisture Content and Fresh Property Control Measures inCementitious Mortars","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Oak Ridge National Laboratory; Virginia Polytechnic Institute and State University","keywords":"Mortar; Aggregate (composite); Cementitious; Water content; Moisture; Materials science; Composite material; Property (philosophy); Environmental science; Pulp and paper industry; Geotechnical engineering; Cement; Geology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001410923,0.0006178171,0.0003298913,0.0006669568,0.0003128189,0.0005324508,0.0005586761,0.0003453699,0.0009251178],"category_scores_gemma":[0.003242414,0.0002089889,0.0004341348,0.0004745891,0.0003300973,0.0005319037,0.0002600074,0.0004631858,0.0001988273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005316716,"about_ca_system_score_gemma":0.0002316436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002842514,"about_ca_topic_score_gemma":0.005728679,"domain_scores_codex":[0.9980946,0.0002921485,0.0001660182,0.0004070823,0.000949619,0.00009051494],"domain_scores_gemma":[0.9956969,0.001217909,0.001521774,0.0004871552,0.0009803473,0.00009597353],"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":[0.001260519,0.0004466893,0.07573491,0.0001931178,0.000147334,0.00008867535,0.0002473493,0.006682567,0.8644344,0.0002159416,0.0001413028,0.05040722],"study_design_scores_gemma":[0.00001830014,0.003576348,0.1826879,0.00001238623,0.0001515417,0.0001202538,0.0001189042,0.006695373,0.8053812,0.00009844255,0.001085373,0.00005384991],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643608,0.0009421915,0.03209457,0.00003287828,0.00004199293,0.0001218285,0.0003979107,0.0001808568,0.001826959],"genre_scores_gemma":[0.9912579,0.0001058572,0.007660785,0.00001720095,0.00001191266,0.00003639403,0.0001545503,0.00002860387,0.0007268013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002842514,"threshold_uncertainty_score":0.007461727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02257662877382223,"score_gpt":0.2184094384408728,"score_spread":0.1958328096670506,"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."}}