{"id":"W7123390735","doi":"10.3997/2214-4609.202576027","title":"AI-Driven Petrophysical Interpretation of Subsurface Data for Reservoir Characterization: A Case Study from the Indus Basin","year":2025,"lang":"","type":"article","venue":"","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Indus; Petrophysics; Structural basin; Reservoir modeling; Oil shale; Interpretation (philosophy); Transformation (genetics)","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":[0.0004485811,0.0003216039,0.0002343035,0.0009812906,0.0005550904,0.000865059,0.0006233099,0.0004051269,0.0009381432],"category_scores_gemma":[0.001120322,0.0001582541,0.0002604942,0.001391631,0.0005848848,0.0005552343,0.0005251913,0.000376342,0.0002002306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008304457,"about_ca_system_score_gemma":0.001262006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03390597,"about_ca_topic_score_gemma":0.05963066,"domain_scores_codex":[0.9997604,0.00006176102,0.00001950542,0.00002919491,0.00009679858,0.00003227531],"domain_scores_gemma":[0.999276,0.0003556727,0.00006173256,0.00007199346,0.0001949175,0.00003977916],"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":[0.0004303599,0.0004835629,0.2719864,0.0004314999,0.0001294732,0.01187823,0.002915259,0.4637325,0.02999761,0.00507668,0.004231471,0.2087069],"study_design_scores_gemma":[0.00003294466,0.00008535999,0.07740057,0.0000577073,0.00003824525,0.0006823217,0.004157453,0.8871915,0.02186126,0.003414323,0.005014281,0.00006397596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855903,0.00004653649,0.01011639,0.0003484902,0.000008012435,0.00005212481,0.0005489112,0.0001501151,0.003139203],"genre_scores_gemma":[0.9853156,0.0000554947,0.01368403,0.00001921181,0.000005182276,0.00001626402,0.000249742,0.00001670723,0.0006377544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03390597,"threshold_uncertainty_score":0.06741726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322679360781092,"score_gpt":0.3014387707683535,"score_spread":0.2691708346902443,"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."}}