{"id":"W2748534211","doi":"10.1071/aj99030","title":"BENCHMARKING TO SET FIELD-LEVEL COST SAVINGS TARGETS AND SUCCESSFUL METHODS TO REDUCE FIELD OPERATING COSTS","year":2000,"lang":"en","type":"article","venue":"The APPEA Journal","topic":"Marine and Offshore Engineering Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remedial action; Benchmarking; Cash flow; Submarine pipeline; Resource (disambiguation); Remedial education; Business; Operations research; Environmental resource management; Operations management; Computer science; Environmental science; Engineering; Finance; Geology; Oceanography; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006592038,0.0001889869,0.0002166998,0.00007714082,0.0003012285,0.0001736922,0.0002619261,0.00005192156,0.0004046736],"category_scores_gemma":[0.0001793434,0.0001440993,0.0000450108,0.000181491,0.000009112952,0.0001077962,0.0001082237,0.0004396305,0.0000181869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004922387,"about_ca_system_score_gemma":0.000009778327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007099098,"about_ca_topic_score_gemma":0.00003581768,"domain_scores_codex":[0.9990468,0.00004205395,0.000262411,0.0001425592,0.0001410198,0.0003651283],"domain_scores_gemma":[0.9992912,0.0003044846,0.00001957964,0.0001729382,0.0000378229,0.0001739978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002473092,0.000006484519,0.0008468589,0.00003259357,0.0001075018,0.00002507108,0.003133565,0.03497188,0.004338852,0.0000671992,0.04794371,0.9085016],"study_design_scores_gemma":[0.001740845,0.001057583,0.03761942,0.00144676,0.0002203814,0.00188512,0.002157765,0.07835487,0.09405661,0.0005177615,0.7783101,0.002632751],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7422301,0.001764866,0.2301491,0.006099754,0.00116547,0.0004803049,0.000008206027,0.000185939,0.01791628],"genre_scores_gemma":[0.9212698,0.0004727616,0.07466904,0.001850167,0.001128439,0.00002811383,0.000001540267,0.00004615221,0.0005340372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9058688,"threshold_uncertainty_score":0.5876198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841642041658665,"score_gpt":0.3012629395801081,"score_spread":0.2828465191635215,"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."}}