{"id":"W2760939880","doi":"10.2118/187379-ms","title":"A Meta-Data Framework for Transparency in Rate of Penetration Calculations","year":2017,"lang":"en","type":"article","venue":"SPE Annual Technical Conference and Exhibition","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apache (Canada)","funders":"University of Texas at Austin","keywords":"Computer science; Data mining; Data type; Transparency (behavior); Process (computing)","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":[0.0002238231,0.00008791029,0.0001897128,0.00004939805,0.00005849234,0.00003960459,0.0001562199,0.0001075611,0.0000147951],"category_scores_gemma":[0.00009811595,0.00008383465,0.00003787665,0.00004059678,0.00004105878,0.0003370572,0.00002075311,0.0001139145,0.000001036332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007198376,"about_ca_system_score_gemma":0.00000985205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004195036,"about_ca_topic_score_gemma":0.0001603112,"domain_scores_codex":[0.9994671,0.000007390053,0.0002102184,0.0001501041,0.00004909731,0.0001161115],"domain_scores_gemma":[0.9994918,0.00005931043,0.00003542958,0.0003403822,0.00004112731,0.00003192195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001596671,0.0002755011,0.002103709,0.001761321,0.0006866962,0.0000139879,0.001686963,0.1332661,0.09817605,0.7025004,0.001437051,0.05793259],"study_design_scores_gemma":[0.00113058,0.0002611347,0.05062414,0.000675087,0.0006982464,0.000006046826,0.0001713634,0.704065,0.01685452,0.223023,0.001708961,0.0007819099],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05413341,0.0002290327,0.9436738,0.0002961985,0.0000834364,0.0002463501,0.0002739627,0.0001161198,0.0009476438],"genre_scores_gemma":[0.9913813,0.000244981,0.008202814,0.000006491052,0.00003464763,0.00002826013,0.00008317745,0.00000945868,0.000008838706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9372479,"threshold_uncertainty_score":0.3418678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1243446000101526,"score_gpt":0.3198239654109095,"score_spread":0.1954793654007568,"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."}}