{"id":"W2538049468","doi":"10.1115/ipc2000-155","title":"Multi-Pipeline Geographical Information System Based on High Accuracy Inertial Surveys","year":2000,"lang":"en","type":"article","venue":"","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services","funders":"","keywords":"Pipeline (software); Computer science; Pipeline transport; Geographic information system; Software; Plan (archaeology); Data mining; Remote sensing; Geology; Engineering; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001017961,0.0007341155,0.0008263687,0.00596636,0.0007316048,0.001408703,0.001085322,0.0006022471,0.01191292],"category_scores_gemma":[0.002472475,0.0004620386,0.0004368382,0.006081688,0.0002766428,0.002400092,0.001690073,0.0005319131,0.006664169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001117807,"about_ca_system_score_gemma":0.001956337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02012187,"about_ca_topic_score_gemma":0.01407242,"domain_scores_codex":[0.9991266,0.0001474594,0.000110937,0.0002197501,0.0003209632,0.00007434513],"domain_scores_gemma":[0.9980228,0.0002098032,0.0002749088,0.0004945251,0.0008500539,0.0001478548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006193524,0.0001964855,0.02819746,0.0007603184,0.0001734103,0.0004732686,0.0009475961,0.02998971,0.01883834,0.02120826,0.2184949,0.6801009],"study_design_scores_gemma":[0.0002886311,0.0003418706,0.06638382,0.0002203207,0.000210714,0.0005765687,0.0006465261,0.2304056,0.02645831,0.008347251,0.6658888,0.0002314207],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02583865,0.0004481254,0.7907502,0.000417855,0.0001885901,0.0008640265,0.06147885,0.09138693,0.02862686],"genre_scores_gemma":[0.2653135,0.0007143015,0.5606877,0.0001665112,0.0002036343,0.002026427,0.1487056,0.001810363,0.02037192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02012187,"threshold_uncertainty_score":0.0400095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005552584549891487,"score_gpt":0.1896403595221689,"score_spread":0.1840877749722774,"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."}}