{"id":"W3035017199","doi":"10.1190/int-2019-0169.1","title":"Sedimentary sequence and architecture analysis by integrating multidiscipline data — An example of a sandy conglomerate reservoir in the Qie12 block, Qaidam Basin, northwest China","year":2020,"lang":"en","type":"article","venue":"Interpretation","topic":"Geological formations and processes","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"National Science and Technology Major Project","keywords":"Geology; Alluvial fan; Sedimentary rock; Conglomerate; Petrophysics; Alluvium; Architecture; Geomorphology; Sedimentary structures; Structural basin; Channel (broadcasting); Sequence (biology); Petrology; Paleontology; Facies; Geotechnical engineering; Archaeology; Porosity; Engineering","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":[0.0003763367,0.00009278692,0.0001583633,0.00006381505,0.00008538169,0.00006455887,0.0003367629,0.00003141896,0.0001754086],"category_scores_gemma":[0.0001111209,0.00005584601,0.00002046403,0.0005918512,0.00007696368,0.0004552578,0.00003208111,0.0001483629,0.000002227204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001410781,"about_ca_system_score_gemma":0.00001624649,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02902518,"about_ca_topic_score_gemma":0.04487482,"domain_scores_codex":[0.9990736,0.000163562,0.00026489,0.000245129,0.000146251,0.0001066071],"domain_scores_gemma":[0.9994034,0.0002047186,0.0001079635,0.0001989282,0.00003256897,0.00005246541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001455705,0.00003593613,0.8942361,0.00006527716,0.00007335478,0.000004354587,0.02934371,0.04364931,0.0003121268,0.00001275457,0.00008216522,0.0320393],"study_design_scores_gemma":[0.000156652,0.0002592861,0.36448,0.00002012013,0.0000683939,0.000004369841,0.002427039,0.6319129,0.00009790687,0.0002096718,0.0002687878,0.00009479469],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943766,0.0002508516,0.002993832,0.001377724,0.00001475398,0.0001325497,0.0006748484,0.0000119377,0.0001669202],"genre_scores_gemma":[0.9934908,0.00002507863,0.001855966,0.0005092931,0.00001457301,0.00000159916,0.004099747,0.000001238578,0.000001679793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5882636,"threshold_uncertainty_score":0.9774407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04224407943958047,"score_gpt":0.2740443529632444,"score_spread":0.2318002735236639,"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."}}