{"id":"W4384935110","doi":"10.24425/mms.2021.137134","title":"Trajectory determination for pipelines using an inspection robot and pipeline features","year":2021,"lang":"en","type":"article","venue":"Metrology and Measurement Systems","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Mitacs","keywords":"Pipeline transport; Pipeline (software); Trajectory; Computer science; Robot; Marine engineering; Artificial intelligence; Computer vision; Engineering; Mechanical engineering; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001945844,0.0004428457,0.0003168239,0.0005214098,0.0003747871,0.000227015,0.0003911264,0.0003684421,0.0007328895],"category_scores_gemma":[0.0007724874,0.0002499922,0.0002928544,0.0005622079,0.0003661612,0.000743408,0.0004288843,0.0003824833,0.0002867428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003650934,"about_ca_system_score_gemma":0.0008844665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006531117,"about_ca_topic_score_gemma":0.00515419,"domain_scores_codex":[0.9997637,0.00002750831,0.00001023798,0.00008732442,0.0000910229,0.00002014694],"domain_scores_gemma":[0.9996444,0.00005248279,0.00009312733,0.00006211764,0.0001321472,0.00001581333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003401038,0.00006794081,0.01163029,0.0003052688,0.00007401842,0.0004638734,0.0006315961,0.2215127,0.1751167,0.006390214,0.002983846,0.5804834],"study_design_scores_gemma":[0.00002690832,0.0002175239,0.007622634,0.00002135679,0.00003472224,0.0004808848,0.0001192705,0.9472184,0.03787616,0.001460451,0.004868811,0.00005282063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03427256,0.00008965525,0.9640988,0.00004470077,0.00001400203,0.00001588214,0.00004580584,0.000925543,0.0004931124],"genre_scores_gemma":[0.6187015,0.0001744785,0.3786702,0.00002348379,0.00001312093,0.00003854331,0.0002416362,0.00006298557,0.002074013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006531117,"threshold_uncertainty_score":0.01298618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06035514589318156,"score_gpt":0.2879158678915461,"score_spread":0.2275607219983646,"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."}}