{"id":"W2410749303","doi":"10.1109/plans.2016.7479678","title":"Pipeline junction detection from accelerometer measurement using fast orthogonal search","year":2016,"lang":"en","type":"article","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"","keywords":"Pipeline (software); Accelerometer; Inertial measurement unit; Azimuth; Pipeline transport; Computer science; Real-time computing; Inertial navigation system; Simulation; Engineering; Acoustics; Inertial frame of reference; Computer vision; Mechanical engineering; Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001383836,0.00009290515,0.00007575549,0.00007083821,0.00004890444,0.00001992369,0.0000375281,0.00006327884,0.0004867403],"category_scores_gemma":[0.00001216861,0.0000644187,0.00003944392,0.0001156464,0.000009561917,0.0001854863,0.000009850372,0.00006283077,0.0001215898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002144922,"about_ca_system_score_gemma":0.000006119799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002237621,"about_ca_topic_score_gemma":0.0001522778,"domain_scores_codex":[0.9992384,0.00002136529,0.0001556729,0.0001255525,0.000298987,0.0001599809],"domain_scores_gemma":[0.9997296,0.00001413726,0.00001137743,0.00009915799,0.00009964455,0.00004613442],"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":[0.00001730548,0.000006142368,0.0001571022,0.000003472722,0.00001321654,4.154932e-7,0.00001674072,0.0018012,0.8658197,0.000004427633,0.00006725813,0.1320931],"study_design_scores_gemma":[0.00037756,0.00001850038,0.005106503,0.00002648348,0.00001531756,0.000002040249,0.0000132295,0.1083357,0.885313,0.000046752,0.0006141078,0.0001307925],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.605041,0.00001390875,0.3934856,0.00001786302,0.0003769495,0.00005607583,0.00000293472,0.0001460603,0.000859654],"genre_scores_gemma":[0.9987543,0.00000839408,0.0006763708,0.0000136747,0.0003936236,0.000003138709,0.000004687514,0.00002012165,0.0001256401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3937134,"threshold_uncertainty_score":0.5329465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04847200936959484,"score_gpt":0.2287529034697096,"score_spread":0.1802808941001148,"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."}}