{"id":"W3165284378","doi":"10.2118/202073-ms","title":"Accurate Drilling Data Interpretations Brought Significant Values to a Major Drilling Project","year":2021,"lang":"en","type":"article","venue":"SPE/IADC Middle East Drilling Technology Conference and Exhibition","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Drilling; Normalization (sociology); Categorization; Coding (social sciences); Data mining; Data collection; Data science; Engineering; Artificial intelligence; Statistics","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":[0.0003408458,0.0005059241,0.0005620107,0.0006784067,0.0003172332,0.0003039218,0.0005517031,0.0003996784,0.00004153778],"category_scores_gemma":[0.0002702426,0.0005572176,0.00008302659,0.001168177,0.0001441308,0.0005498576,0.0003487542,0.0006412567,0.00009349701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009034161,"about_ca_system_score_gemma":0.0001256594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003002206,"about_ca_topic_score_gemma":0.0001052114,"domain_scores_codex":[0.9972386,0.00004668921,0.0006715572,0.001003152,0.0002666513,0.0007732997],"domain_scores_gemma":[0.9982719,0.00009463018,0.00009725318,0.0010802,0.0002821261,0.0001738964],"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":[0.0001124379,0.0002813615,0.001640685,0.001895196,0.001042925,0.0005129252,0.01131069,0.5271416,0.3168291,0.02657813,0.001781865,0.110873],"study_design_scores_gemma":[0.0005701788,0.0000920365,0.00004160718,0.001902995,0.0001469997,0.0001403787,0.003909612,0.9365717,0.04407815,0.005970042,0.005517901,0.001058421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2316038,0.001765146,0.7605963,0.0008344583,0.0009437716,0.0004908053,0.0001672369,0.002169324,0.001429207],"genre_scores_gemma":[0.9699271,0.001014647,0.02793191,0.00007478907,0.0002713695,0.00007257087,0.0004182659,0.0001014038,0.0001879469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7383233,"threshold_uncertainty_score":0.9996879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05560488414319653,"score_gpt":0.2572248499730507,"score_spread":0.2016199658298542,"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."}}