{"id":"W2068217738","doi":"10.1115/ipc2006-10173","title":"Prediction of the Location and Duration of Water Condensation in Nominally Dry Gas Transmission Pipelines","year":2006,"lang":"en","type":"article","venue":"Volume 2: Integrity Management; Poster Session; Student Paper Competition","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada); Nova Chemicals (Canada)","funders":"","keywords":"Corrosion; Dew point; Relative humidity; Water vapor; Condensation; Humidity; Dry gas; Materials science; Inlet; Environmental science; Evaporation; Pipeline transport; Saturation (graph theory); Upset; Mass transfer; Mechanics; Environmental engineering; Metallurgy; Chemistry; Meteorology; Geology","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":[0.0003007354,0.0001694557,0.0001998773,0.0002038523,0.00007150428,0.00004610132,0.0001287822,0.0001074911,0.00004700529],"category_scores_gemma":[0.000003435169,0.0001191484,0.00004997932,0.0002121704,0.0000437419,0.0004728554,0.00006031258,0.0001363635,0.000003998797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008586497,"about_ca_system_score_gemma":0.000005892946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002047611,"about_ca_topic_score_gemma":0.0004366772,"domain_scores_codex":[0.9984696,0.000112756,0.0007316864,0.0002084654,0.0003331563,0.0001443306],"domain_scores_gemma":[0.9994774,0.00001304693,0.0001211983,0.0002064604,0.0001605162,0.0000213388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002599338,0.001159634,0.5263047,0.00556632,0.0002046498,0.000007437951,0.00788673,0.1612872,0.2796786,0.008552925,0.001361198,0.007730668],"study_design_scores_gemma":[0.001204011,0.0000714803,0.9066522,0.001117997,0.00007852858,0.000003403089,0.0006699896,0.06840539,0.02040755,0.0004548903,0.0007473176,0.0001873114],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414898,0.0001045415,0.05399123,0.0003520965,0.0005107127,0.0008115229,0.00001488262,0.00007275404,0.002652428],"genre_scores_gemma":[0.9985959,0.00008225353,0.0004313453,0.00001922574,0.00005898838,0.00003917652,0.0001682306,0.00001847199,0.0005863931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3803474,"threshold_uncertainty_score":0.4858732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007157205157630063,"score_gpt":0.1909629897069559,"score_spread":0.1838057845493258,"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."}}