{"id":"W3023833338","doi":"10.4043/30603-ms","title":"Additive Manufacturing In The Oil &amp; Gas Industry And Status Update On The New API 20S Standard \"Qualification Of Additively Manufactured Metallic Materials For Use In The Petroleum And Natural Gas Industries\"","year":2020,"lang":"en","type":"article","venue":"Offshore Technology Conference","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"","keywords":"Standardization; Petroleum industry; Process (computing); Computer science; Manufacturing engineering; SAFER; Risk analysis (engineering); Engineering management; Engineering; Business; Computer security","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":[0.0003523476,0.0002374863,0.0002987084,0.0001497523,0.00005686185,0.00009338331,0.0003341604,0.0003269526,0.00002809348],"category_scores_gemma":[0.0003154347,0.000146306,0.0000210807,0.0001918313,0.0001709826,0.0001142552,0.00004923484,0.0009320484,0.000001573123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003665199,"about_ca_system_score_gemma":0.00004589067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003510906,"about_ca_topic_score_gemma":0.0001221257,"domain_scores_codex":[0.9988899,0.00007337552,0.0002906827,0.0002552009,0.0001772846,0.00031361],"domain_scores_gemma":[0.9991588,0.0004133227,0.00008498371,0.00026757,0.00003674133,0.00003857126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002016539,0.0002024234,0.002839319,0.001228791,0.001182808,0.0001212538,0.03563487,0.01778396,0.08684421,0.1620587,0.02971779,0.6603693],"study_design_scores_gemma":[0.002829112,0.0004208286,0.01107049,0.0007106753,0.0001645951,0.00005060534,0.01162478,0.009233389,0.8416397,0.007534192,0.113605,0.001116577],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926028,0.0002091774,0.001185538,0.00507176,0.00006654202,0.0002998889,0.0003913481,0.0001055162,0.00006743003],"genre_scores_gemma":[0.9988568,0.0004649542,0.0002721612,0.0001693912,0.00003520792,0.00008702588,0.000078006,0.0000214039,0.00001509115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7547955,"threshold_uncertainty_score":0.5966187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02729117366551949,"score_gpt":0.2292718788425046,"score_spread":0.201980705176985,"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."}}