{"id":"W4393643422","doi":"10.1306/01172320041","title":"Jurassic deep-water reservoirs at a transfer-transform offset: Modeling the mixed carbonate-siliciclastic Shelburne subbasin, southeastern Canadian margin","year":2024,"lang":"en","type":"article","venue":"AAPG Bulletin","topic":"Geological Studies and Exploration","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Saint Mary's University","funders":"","keywords":"Siliciclastic; Geology; Carbonate; Geochemistry; Margin (machine learning); Petrology; Geomorphology; Structural basin; Sedimentary depositional environment; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001928068,0.000650868,0.0003318337,0.0005533485,0.001022619,0.0009908567,0.001162492,0.00120609,0.002175217],"category_scores_gemma":[0.000593911,0.0004831149,0.0006054072,0.0003840857,0.0006642931,0.0002677134,0.0004237042,0.000598197,0.0001092378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006022263,"about_ca_system_score_gemma":0.004785117,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8466778,"about_ca_topic_score_gemma":0.8213258,"domain_scores_codex":[0.9999329,0.00000742563,0.000002952284,0.0000185454,0.00001126014,0.00002697264],"domain_scores_gemma":[0.9997414,0.00007711606,0.00003088621,0.00001263509,0.00007797436,0.00006006871],"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":[0.00008782947,0.00007959621,0.02357838,0.00002074531,0.00003270662,0.00013459,0.00004552719,0.9727421,0.001165344,0.0003574418,0.0002346152,0.001521114],"study_design_scores_gemma":[0.00001970468,0.00002042241,0.005984249,0.000003544497,0.00001374908,0.000007268834,0.00005226727,0.9933668,0.0003093515,0.00004032963,0.000176436,0.000005981906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972849,0.00003291677,0.0005459783,0.0000484226,0.00000539556,0.00001677267,0.0004368468,0.00005240197,0.001576448],"genre_scores_gemma":[0.9977795,0.00002349998,0.0008797713,0.0000126768,0.000002209383,0.00001119253,0.0002272056,0.00001075559,0.001052983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1533222,"threshold_uncertainty_score":0.3084502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01791678701494122,"score_gpt":0.1831027819778253,"score_spread":0.1651859949628841,"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."}}