{"id":"W2807749681","doi":"10.4018/ijssci.2018070103","title":"Application of Structural Properties of Seismic Data to Prediction of Hydrocarbon Distribution","year":2018,"lang":"en","type":"article","venue":"International Journal of Software Science and Computational Intelligence","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Comparability; Petroleum engineering; Petroleum; Geology; Computer science; Facies; Fossil fuel; Block (permutation group theory); Structural basin; Geomorphology","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":[0.0003489871,0.0005914149,0.0002719852,0.001873699,0.000149272,0.0003491264,0.0002416029,0.0003848462,0.0006481193],"category_scores_gemma":[0.002911597,0.000250042,0.0003024992,0.001202105,0.000179015,0.0006863199,0.0002606336,0.0003667517,0.0003670971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002646811,"about_ca_system_score_gemma":0.0003688617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003375457,"about_ca_topic_score_gemma":0.003575357,"domain_scores_codex":[0.9998168,0.00003675269,0.00001242122,0.00004525938,0.00007362918,0.00001517554],"domain_scores_gemma":[0.998706,0.0006426148,0.0001855037,0.0001027909,0.0003136515,0.00004946244],"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":[0.0001610019,0.0001256836,0.05489826,0.0001378576,0.00007694613,0.0001474852,0.00006899598,0.609247,0.02811414,0.00169718,0.000894132,0.3044313],"study_design_scores_gemma":[0.00000190273,0.00002190211,0.005822589,0.000004729126,0.000008144963,0.00002382429,0.00001422301,0.9894429,0.003764638,0.0006056434,0.0002854868,0.000003998238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3788164,0.0004078129,0.6163053,0.0002261733,0.00003959024,0.00004208941,0.001122268,0.0009483295,0.002092011],"genre_scores_gemma":[0.9447947,0.0002469609,0.05346181,0.00001102059,0.00003006262,0.00002202031,0.0008595346,0.00003690695,0.0005369876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003375457,"threshold_uncertainty_score":0.006711662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04306730036485026,"score_gpt":0.3041778601560872,"score_spread":0.261110559791237,"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."}}