{"id":"W4389941213","doi":"10.1016/j.jobe.2023.108328","title":"Development of a machine learning model for on-site evaluation of concrete compressive strength by SonReb","year":2023,"lang":"en","type":"article","venue":"Journal of Building Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cimetrix Solutions (Canada); University of Ottawa","funders":"","keywords":"Compressive strength; Engineering; Structural engineering; Geotechnical engineering; Materials science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007393132,0.0001376796,0.0002933879,0.0002729086,0.00003210192,0.000009584821,0.0001137669,0.0000550563,0.000001958302],"category_scores_gemma":[0.0001710303,0.0001309193,0.00008789814,0.0001544493,0.000006986436,0.00009993617,0.00002028404,0.0002285426,2.284208e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001221621,"about_ca_system_score_gemma":0.0000445716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.819226e-7,"about_ca_topic_score_gemma":2.479992e-7,"domain_scores_codex":[0.9988241,0.00000913645,0.0005076507,0.00007349057,0.0003826465,0.0002029359],"domain_scores_gemma":[0.9993112,0.0001099145,0.0002173001,0.00007120221,0.0002434669,0.00004688922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001166293,0.000001247856,0.00003811745,0.0001086539,0.00007026716,5.33147e-7,0.000659717,0.6738118,0.3218929,0.00002801933,0.0001096019,0.003267543],"study_design_scores_gemma":[0.000571411,0.00003252383,0.00008999246,0.0003761083,0.00003690952,0.000002917042,0.00005302432,0.8011168,0.1972513,0.00001575459,0.0003596916,0.00009351194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.793541,0.0002374944,0.2057235,0.000003876915,0.0003275711,0.0000914643,0.00001281198,0.00004497204,0.00001734017],"genre_scores_gemma":[0.9464838,0.00003013732,0.05333658,0.000001319182,0.00008996311,0.00000677618,0.000007185106,0.00003648481,0.000007737813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1529429,"threshold_uncertainty_score":0.5338735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0192256538676538,"score_gpt":0.2612323145142481,"score_spread":0.2420066606465943,"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."}}