{"id":"W2784450541","doi":"10.3968/10087","title":"The Bit Selection Research on LS101","year":2017,"lang":"en","type":"article","venue":"Advances in petroleum exploration and development","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bit (key); Block (permutation group theory); Drilling; Computer science; Selection (genetic algorithm); Geology; Drill; Petroleum engineering; Artificial intelligence; Engineering; Mathematics; Mechanical engineering; Computer network; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004203884,0.0003493768,0.0003828402,0.001104979,0.0004925485,0.0006040504,0.0003082314,0.0002678028,0.003710606],"category_scores_gemma":[0.001080284,0.0001797387,0.0003725608,0.001271351,0.0002901935,0.0008956895,0.0004149685,0.0002205384,0.0006019113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004571057,"about_ca_system_score_gemma":0.0005344246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003967335,"about_ca_topic_score_gemma":0.007138479,"domain_scores_codex":[0.999311,0.00008048087,0.00004371323,0.000116703,0.0003648013,0.0000833041],"domain_scores_gemma":[0.9990689,0.0001835773,0.0001171764,0.00009139886,0.0004689787,0.00006992712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002159171,0.0002656483,0.271511,0.000972405,0.0001016409,0.001209125,0.0009440831,0.04860551,0.2430693,0.005059861,0.004907697,0.4211946],"study_design_scores_gemma":[0.000119703,0.004130963,0.3939313,0.0001358408,0.0004022558,0.001807203,0.003250666,0.2068868,0.351334,0.003345531,0.03446906,0.000186634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820845,0.0004135021,0.01198897,0.00007284893,0.00001681517,0.00004441409,0.0004149493,0.00009559769,0.004868409],"genre_scores_gemma":[0.9879556,0.0003638364,0.006315556,0.00002378732,0.000004539271,0.0000227775,0.0007642374,0.00002436404,0.004525092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003967335,"threshold_uncertainty_score":0.0124132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05236221023856508,"score_gpt":0.3276432867671336,"score_spread":0.2752810765285685,"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."}}