{"id":"W4200181135","doi":"10.1109/sensors47087.2021.9639721","title":"Enabling Real-time Estimation of Borehole Parameters in Deep Drilling","year":2021,"lang":"en","type":"article","venue":"2021 IEEE Sensors","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Borehole; Drilling; Torque; Measurement while drilling; Work (physics); Wellbore; Geology; Field (mathematics); Dynamical friction; Engineering; Petroleum engineering; Geotechnical engineering; Mechanical engineering","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":[0.0001474843,0.0001454174,0.0002513631,0.000155469,0.00001948645,0.00002258151,0.00006327714,0.00008772439,0.00003442052],"category_scores_gemma":[0.00007327847,0.0001747376,0.00007153445,0.0004391446,0.00001478515,0.00008990195,0.000009705866,0.0001503306,0.00004548643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006604483,"about_ca_system_score_gemma":0.00001433941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004302336,"about_ca_topic_score_gemma":0.00001048789,"domain_scores_codex":[0.9990699,0.00002404688,0.0003223867,0.0001803161,0.0001422867,0.0002610696],"domain_scores_gemma":[0.9995332,0.0001208196,0.0000302522,0.0002236205,0.00003542437,0.00005663103],"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":[0.000001661406,0.000008659329,0.00005316197,0.00007666771,0.00002151474,0.00003714592,0.0003808661,0.9394684,0.05608965,0.00001534244,0.00002622081,0.003820702],"study_design_scores_gemma":[0.0001402118,0.000005206654,0.0001070428,0.0001186131,0.00001009411,0.000005628236,0.0000962531,0.782184,0.2170784,0.0000378997,0.00007526417,0.0001413969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790457,0.0002415646,0.01789993,0.00001241147,0.000404834,0.00005787316,0.000003813565,0.0001383334,0.002195571],"genre_scores_gemma":[0.9817032,0.0003957984,0.01764124,0.000004079549,0.00005728491,0.000003734429,0.00001928598,0.00004740316,0.0001280181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1609887,"threshold_uncertainty_score":0.7125593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0073531292878939,"score_gpt":0.2005531642442109,"score_spread":0.193200034956317,"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."}}