{"id":"W2902002006","doi":"","title":"Assessment of Flatbed Scanner Method for Quality Assurance Testing of Air Content and Spacing Factor in Concrete","year":2013,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Engineering Applied Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministère des Transports","keywords":"Scanner; Quality assurance; Content (measure theory); Engineering; Forensic engineering; Reliability engineering; Computer science; Artificial intelligence; Mathematics; Operations management","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.002110442,0.0005031049,0.0003324623,0.0009968916,0.0002452878,0.0004026992,0.0006910533,0.0006627694,0.001168603],"category_scores_gemma":[0.002823754,0.0004218557,0.0003207842,0.0004336883,0.0004454124,0.0004212467,0.0005128155,0.0003097621,0.0003670422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003275724,"about_ca_system_score_gemma":0.0005611013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001414364,"about_ca_topic_score_gemma":0.004889768,"domain_scores_codex":[0.9971877,0.0005402741,0.000096555,0.0003901889,0.001709038,0.00007631889],"domain_scores_gemma":[0.9958378,0.001181395,0.0004890255,0.0004794708,0.001912032,0.0001003727],"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":[0.0002734421,0.00008045702,0.005313781,0.0001979094,0.00002633962,0.00009997189,0.0001637986,0.001207456,0.9547104,0.0001594843,0.0001376931,0.03762923],"study_design_scores_gemma":[0.00003847293,0.003364516,0.04576744,0.00004306373,0.0000993609,0.00130045,0.0002379073,0.01722866,0.9292856,0.000187738,0.00235288,0.00009393872],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.79533,0.003251669,0.1976207,0.00009391289,0.0000972227,0.000296936,0.0002518304,0.0004436247,0.002614108],"genre_scores_gemma":[0.8143677,0.00119904,0.1814128,0.00005444328,0.00001635782,0.00013323,0.0002490047,0.00005734787,0.002510242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002110442,"threshold_uncertainty_score":0.01116121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07365047488232637,"score_gpt":0.4131835577542063,"score_spread":0.33953308287188,"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."}}