{"id":"W2040762839","doi":"10.1016/j.powtec.2008.08.020","title":"Detection of oversized material in a hydrotransport slurry pipe using a non-invasive acoustic method","year":2008,"lang":"en","type":"article","venue":"Powder Technology","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Slurry; Pipeline transport; Materials science; Acoustics; Geotechnical engineering; Geology; Composite material; Engineering; Mechanical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0000629483,0.00009583096,0.0002221232,0.0002325129,0.00004404629,0.000001511568,0.00009525163,0.0001789059,0.00001299417],"category_scores_gemma":[0.00002774709,0.0001081575,0.00003920088,0.0005318138,0.00008303359,0.000037281,0.00001544258,0.0001478675,0.000003920244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004136594,"about_ca_system_score_gemma":0.00002046842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001223156,"about_ca_topic_score_gemma":0.00003238081,"domain_scores_codex":[0.9994192,0.00001696392,0.0001882698,0.0001354193,0.00005724655,0.0001829077],"domain_scores_gemma":[0.999693,0.00004611541,0.00003350746,0.000181094,0.00002386975,0.00002239541],"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":[0.000008206527,0.00002548484,0.0001175645,0.00003392491,0.00001218174,0.000007170141,0.0001414341,0.001946373,0.9961649,0.00009379089,0.000001072342,0.001447888],"study_design_scores_gemma":[0.0003761284,0.00002946585,0.00210239,0.00002315185,0.0000243912,0.00002917061,0.0001016128,0.01045079,0.9838629,0.002752362,0.0001197692,0.00012784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7609363,0.00001655974,0.2385671,0.00002935902,0.00007525778,0.0001517331,0.000005182179,0.0001279786,0.00009057727],"genre_scores_gemma":[0.9514019,0.00003899407,0.04845455,0.000006113231,0.00002509377,0.00004947217,0.000001384967,0.00001774797,0.000004678122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1904657,"threshold_uncertainty_score":0.4410535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01319354352973389,"score_gpt":0.2529514235451074,"score_spread":0.2397578800153735,"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."}}