{"id":"W2010059622","doi":"10.4043/24789-ms","title":"Spatial AHP Enables Highly Effective Pipeline Routing Evaluations","year":2014,"lang":"en","type":"article","venue":"Offshore Technology Conference-Asia","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intecsea (Canada)","funders":"","keywords":"Computer science; Analytic hierarchy process; Geomatics; Pipeline (software); Robustness (evolution); Operations research; Routing (electronic design automation); Geographic information system; Data mining; Engineering; Geography; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003585126,0.000479029,0.0005519723,0.0007540214,0.0001709097,0.00006672519,0.0006820458,0.0007614743,0.00009487638],"category_scores_gemma":[0.0006633232,0.000471275,0.0001019403,0.0007370675,0.0003061308,0.0001300271,0.0001732148,0.0008593801,0.0001743137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001335863,"about_ca_system_score_gemma":0.0000462777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002785678,"about_ca_topic_score_gemma":0.0001199877,"domain_scores_codex":[0.9980325,0.00004413081,0.0004465165,0.0004990328,0.0002601594,0.0007176623],"domain_scores_gemma":[0.9986464,0.000175959,0.00007751902,0.0008156768,0.0001997343,0.00008465173],"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":[0.00001261101,0.00007493536,0.005888444,0.0001080387,0.0001924706,0.00001803003,0.0001693206,0.006428023,0.01876375,0.119082,0.004597505,0.8446649],"study_design_scores_gemma":[0.001680165,0.0005470086,0.009575451,0.000372087,0.0002338747,0.00008708458,0.0009662021,0.6559864,0.2546468,0.03259749,0.04157584,0.001731634],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3945137,0.0007758957,0.537946,0.002444851,0.002402732,0.001141998,0.00003871225,0.02008224,0.04065378],"genre_scores_gemma":[0.9953043,0.00007301212,0.003763751,0.00001194355,0.0001718646,0.0002594951,0.00004059342,0.00008192618,0.0002931269],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8429333,"threshold_uncertainty_score":0.9997739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009086249520877656,"score_gpt":0.2267482809685205,"score_spread":0.2176620314476428,"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."}}