{"id":"W2074440952","doi":"10.1115/ipc2004-0362","title":"Spatially Enabled Pipeline Route Optimization Model","year":2004,"lang":"en","type":"article","venue":"2004 International Pipeline Conference, Volumes 1, 2, and 3","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Pipeline (software); Computer science; Pipeline transport; Hazard; Risk analysis (engineering); Process (computing); Routing (electronic design automation); Operations research; Engineering","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":[0.0001080025,0.0002264544,0.0002157244,0.0001374939,0.00006686027,0.0001455145,0.0002020176,0.0001190775,0.0006962615],"category_scores_gemma":[0.00006494112,0.0002262513,0.00005339659,0.00008066496,0.00006364674,0.0002216868,0.00005209888,0.0001770035,0.00002855207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008004203,"about_ca_system_score_gemma":0.0001107147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002008976,"about_ca_topic_score_gemma":0.0001917927,"domain_scores_codex":[0.9988408,0.000007713279,0.0004080974,0.0002498009,0.0002540272,0.0002395751],"domain_scores_gemma":[0.999328,0.00001394722,0.00006342417,0.0001600847,0.0003145717,0.0001199912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001363026,0.00004366097,0.0002580695,0.00002292483,0.00002480256,0.000009637763,0.00008153161,0.9803352,0.00005207615,0.009203855,0.003265303,0.006689322],"study_design_scores_gemma":[0.0008882125,0.00001747684,0.0001013891,0.00004738458,0.00002584799,0.00001346358,0.00001862734,0.9854242,0.00008465234,0.004687076,0.008425539,0.0002661749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002295783,0.0002381554,0.9462872,0.0005232804,0.0005841454,0.0001387242,0.0001279371,0.0002191049,0.04958567],"genre_scores_gemma":[0.9650655,0.0007378,0.02292632,0.0002135156,0.00044358,0.00001478568,0.000468082,0.00003488116,0.01009555],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9627697,"threshold_uncertainty_score":0.922626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338469445398051,"score_gpt":0.2174036850021744,"score_spread":0.2040189905481939,"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."}}