{"id":"W3015165961","doi":"10.1007/s12303-019-0046-3","title":"Application of Multi-Resolution Graph-based Clustering for electrofacies prediction: a case study from the Horn River Shale, British Columbia, Canada","year":2020,"lang":"en","type":"article","venue":"Geosciences Journal","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Facies; Coring; Geology; Oil shale; Lithology; Seismic attribute; Reservoir modeling; Structural basin; Drilling; Petrology; Petroleum engineering; Paleontology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002109997,0.00006290229,0.0001234655,0.00002505724,0.000441,0.0001890569,0.0001982948,0.00002494931,0.00001564625],"category_scores_gemma":[0.00004298769,0.00006553545,0.00006474821,0.0004316497,0.00006584646,0.0001501886,0.00001450674,0.000132095,2.650958e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005815381,"about_ca_system_score_gemma":0.0001258896,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6082514,"about_ca_topic_score_gemma":0.9581095,"domain_scores_codex":[0.9990819,0.0000426174,0.0002752373,0.000138629,0.0002995555,0.0001620512],"domain_scores_gemma":[0.9995837,0.00004495771,0.00008373024,0.00008692721,0.00009926052,0.0001014098],"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":[0.000007683339,0.00004839135,0.06461193,0.00001555868,0.00008970527,0.0000666997,0.001687862,0.9269332,0.0006977704,1.834924e-7,0.001644321,0.004196672],"study_design_scores_gemma":[0.0004246699,0.0000770666,0.01059102,0.000006880841,0.00004697126,0.0000739094,0.003300346,0.9847978,0.00002741106,0.00000677754,0.0005778139,0.00006928766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5888873,0.0001665087,0.410373,0.0001665586,0.0001148566,0.0001908592,0.00007398,0.00002349403,0.00000345569],"genre_scores_gemma":[0.9987295,0.00002334708,0.0009703038,0.00009547097,0.0001211669,0.00003491167,0.000008431627,0.000006520342,0.00001037887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4098422,"threshold_uncertainty_score":0.3943573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679826460625052,"score_gpt":0.2156174307424869,"score_spread":0.1988191661362363,"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."}}