{"id":"W2048281390","doi":"","title":"MONITORING OF PIPE-WALL THICKNESS AND ITS THINNING RATE BY ULTRASONIC TECHNIQUE","year":2012,"lang":"en","type":"article","venue":"","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"","keywords":"Ultrasonic sensor; Thinning; Materials science; Ultrasonic testing; Measure (data warehouse); Canalisation; Petrochemical; Corrosion; Erosion; Acoustics; Composite material; Geology; Engineering; Computer science; Mechanical engineering; Piping","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":[0.0004960342,0.0001733535,0.0001885707,0.00007596661,0.00003910431,0.00001597984,0.0001397984,0.0001194659,0.0000149949],"category_scores_gemma":[0.0001030094,0.0001687084,0.00003016968,0.0001562878,0.00003275242,0.0003487876,0.00004517084,0.0002449197,0.000003186208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000507356,"about_ca_system_score_gemma":0.000006880824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002649813,"about_ca_topic_score_gemma":2.955227e-7,"domain_scores_codex":[0.9992303,0.00003307864,0.000203449,0.0001242713,0.0001005283,0.0003083579],"domain_scores_gemma":[0.9994833,0.0001719003,0.00004411216,0.0001684392,0.00005167602,0.00008055737],"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":[0.000001508434,0.000009126883,0.0401893,0.000112191,0.00001780655,4.273968e-7,0.0001823181,0.000002437415,0.9573264,0.001830589,0.00007335589,0.0002545481],"study_design_scores_gemma":[0.00007048095,0.00001941329,0.009532812,0.000175388,0.00001388852,0.00002499866,0.00003760671,0.00009701019,0.9864815,0.00329852,0.00004019122,0.0002081291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312181,0.002205791,0.05502697,0.00001546526,0.0001537714,0.0003194819,0.000003702104,0.002225877,0.008830808],"genre_scores_gemma":[0.8147089,0.0001016524,0.1850358,0.000005526957,0.00004295216,0.0000427753,7.677401e-7,0.00004222172,0.00001934011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1300089,"threshold_uncertainty_score":0.6879728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01587551091673253,"score_gpt":0.2481181471100336,"score_spread":0.232242636193301,"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."}}