{"id":"W1506514327","doi":"10.5006/c2001-01633","title":"High Accuracy Pipeline Depth of Cover Survey in Channel Crossing Using Inertial Navigation","year":2001,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services","funders":"","keywords":"Cover (algebra); Pipeline (software); Channel (broadcasting); Inertial navigation system; Computer science; Marine engineering; Inertial frame of reference; Geology; Remote sensing; Acoustics; Engineering; Telecommunications; Mechanical engineering; Physics","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":[0.0002808001,0.0001977831,0.0002188593,0.0008889993,0.0002569261,0.0002745358,0.0002082396,0.0002049739,0.000448306],"category_scores_gemma":[0.0005022567,0.0001510483,0.0001125069,0.0006327095,0.0001722114,0.0002727383,0.0003271196,0.0001309397,0.0001699195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002215703,"about_ca_system_score_gemma":0.0004048288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009160465,"about_ca_topic_score_gemma":0.01892579,"domain_scores_codex":[0.9996814,0.00004876547,0.00000869995,0.00004994306,0.0001511595,0.00006020251],"domain_scores_gemma":[0.9997252,0.00002313603,0.00007048905,0.00003197809,0.000115171,0.00003419702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004418464,0.0002186263,0.4948319,0.000130103,0.00008132963,0.001210734,0.001085097,0.03351606,0.2880138,0.000465641,0.001714883,0.17829],"study_design_scores_gemma":[0.00003684194,0.0005862734,0.8835825,0.00001807577,0.00006390821,0.0006270544,0.0003803932,0.06714043,0.04455204,0.000178681,0.002790159,0.00004372974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985563,0.00004997801,0.01270361,0.00002043311,0.000007626773,0.00001496856,0.0001278255,0.00015602,0.001356452],"genre_scores_gemma":[0.9917258,0.00002248168,0.007804983,0.000005250643,0.000004271438,0.000005025473,0.0001177592,0.000004315363,0.0003101368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009160465,"threshold_uncertainty_score":0.01821429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04062219237557527,"score_gpt":0.2719870334845119,"score_spread":0.2313648411089367,"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."}}