{"id":"W4415787203","doi":"10.1080/12269328.2025.2575390","title":"An interpretable framework for predicting weight-on-bit in horizontal wells based on TCL-BO stacking ensemble","year":2025,"lang":"en","type":"article","venue":"Geosystem Engineering","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Stacking; Pattern recognition (psychology); Scale (ratio); Ensemble learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004192263,0.0009063503,0.000552447,0.0007573651,0.0002557698,0.0005531658,0.0008363349,0.0005994348,0.001279959],"category_scores_gemma":[0.001061204,0.0003291502,0.0005481575,0.0005191274,0.0002487383,0.0008735966,0.0005153568,0.0007241684,0.0002787269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004701051,"about_ca_system_score_gemma":0.0007010825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01144255,"about_ca_topic_score_gemma":0.01587592,"domain_scores_codex":[0.9998887,0.00001920461,0.000006999067,0.00003532195,0.00002621052,0.00002352417],"domain_scores_gemma":[0.9997191,0.00009419151,0.00004489752,0.00001996081,0.0001037554,0.00001797509],"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":[0.00003977822,0.00003638868,0.003253602,0.00002138943,0.00003397768,0.00007185683,0.00003247737,0.9400096,0.002969955,0.001211673,0.0006118958,0.05170745],"study_design_scores_gemma":[6.167629e-7,0.000005164969,0.000214251,0.000001767953,0.000003242699,0.000003638039,0.000002836433,0.9991129,0.0002044782,0.0003965452,0.00005257368,0.000002082131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1608448,0.0004981077,0.8343633,0.0002794808,0.00007378645,0.0000358142,0.0004191009,0.001239399,0.002246105],"genre_scores_gemma":[0.9482822,0.0002237602,0.04942956,0.00007332467,0.00003854116,0.00005763004,0.0004699248,0.00004958245,0.001375566],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01144255,"threshold_uncertainty_score":0.02275187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003989624683678592,"score_gpt":0.2101940899132265,"score_spread":0.2062044652295479,"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."}}