{"id":"W2064676450","doi":"10.4043/22085-ms","title":"Pipeline Routing and Burial Depth Analysis Using GIS Software","year":2011,"lang":"en","type":"article","venue":"OTC Arctic Technology Conference","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering","funders":"","keywords":"Subsea; Submarine pipeline; Pipeline transport; Seabed; Pipeline (software); Marine engineering; Geographic information system; Engineering; Geology; Oceanography; Remote sensing","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":[0.00009159272,0.0002282872,0.0003373949,0.0006796718,0.00007689097,0.00002215965,0.0002918981,0.0003473328,0.0000586191],"category_scores_gemma":[0.0002264488,0.0002322467,0.0000551864,0.0009245419,0.0002223362,0.00008758171,0.0001489936,0.0003936525,0.000008379748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004383322,"about_ca_system_score_gemma":0.00001580328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006914869,"about_ca_topic_score_gemma":0.00005116034,"domain_scores_codex":[0.9990041,0.000007533449,0.0002377712,0.0002921072,0.00008474771,0.000373752],"domain_scores_gemma":[0.9993898,0.00003503485,0.00004346687,0.0004260847,0.00005792943,0.00004770402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003309922,0.0001301538,0.576341,0.0004477167,0.002738509,0.000239656,0.002384311,0.008824325,0.01250081,0.049984,0.0001325983,0.3462439],"study_design_scores_gemma":[0.001651297,0.0002960176,0.04621481,0.000436204,0.002702739,0.0003341619,0.003007844,0.8284143,0.07976287,0.03347464,0.0008972922,0.002807792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6073956,0.0003291288,0.3882759,0.00003803947,0.0001625265,0.00007787304,0.000004632075,0.00318111,0.0005351505],"genre_scores_gemma":[0.9358576,0.00006727449,0.06397796,0.00000361133,0.00001976086,0.00001156377,0.000002986811,0.00002807151,0.000031179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.81959,"threshold_uncertainty_score":0.9470744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02752002308076913,"score_gpt":0.2184439076562563,"score_spread":0.1909238845754872,"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."}}