{"id":"W2924149908","doi":"10.2118/0419-0049-jpt","title":"E&P Leaders Gather for Arctic Technology Conference","year":2019,"lang":"en","type":"article","venue":"Journal of Petroleum Technology","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arctic; Geologist; The arctic; Resource (disambiguation); Political science; Engineering; Environmental resource management; Environmental planning; Business; Oceanography; Geography; Environmental science; Computer science; Geology; Archaeology","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":[0.0001727112,0.0002294451,0.0004951297,0.001607611,0.00002786807,0.00001717449,0.0006507715,0.0005854894,0.00005578652],"category_scores_gemma":[0.0001911523,0.0002086235,0.0001362442,0.0005047071,0.0002051114,0.0001086209,0.00005235913,0.0008066875,0.0000818577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001218333,"about_ca_system_score_gemma":0.00003464178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.580598e-7,"about_ca_topic_score_gemma":0.000003533287,"domain_scores_codex":[0.9987988,0.000004969605,0.0004439888,0.0001626682,0.0001400668,0.000449475],"domain_scores_gemma":[0.9991498,0.00006348959,0.0001410773,0.0004181235,0.0001855481,0.00004196676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000178995,0.0003106882,0.04526985,0.001486507,0.00175758,0.000119183,0.0003624835,0.07923429,0.5763598,0.154258,0.0115679,0.1290946],"study_design_scores_gemma":[0.006101343,0.003435655,0.0009928081,0.0009135632,0.0002886374,0.002756965,0.005805753,0.02071167,0.1480914,0.09744518,0.7115465,0.001910524],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9293103,0.002274798,0.06132295,0.003579892,0.001236563,0.0001602749,0.000005692211,0.001472269,0.0006372501],"genre_scores_gemma":[0.9835016,0.0001778922,0.01578056,0.00001375204,0.00006479031,0.00001935112,9.562888e-7,0.00005515305,0.0003859811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6999786,"threshold_uncertainty_score":0.8507417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01367797304748748,"score_gpt":0.2267969554525938,"score_spread":0.2131189824051063,"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."}}