{"id":"W2170282152","doi":"10.1144/petgeo2011-046","title":"Integrated tectonic basin modelling as an aid to understanding deep-water rifted continental margin structure and location","year":2013,"lang":"en","type":"article","venue":"Petroleum Geoscience","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Continental margin; Tectonics; Palaeogeography; Margin (machine learning); Regional geology; Structural basin; Structural geology; Paleontology; Metamorphic petrology; Geobiology; Magmatism; Telmatology; Seismology; Volcanism","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004123604,0.0007295336,0.00064502,0.0008462528,0.0003544296,0.001848205,0.001188801,0.0008070074,0.003559609],"category_scores_gemma":[0.0009120801,0.0005888122,0.0009953813,0.0009039854,0.0002928874,0.0008859839,0.001263644,0.0006029038,0.0006831175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008132314,"about_ca_system_score_gemma":0.001876986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0234788,"about_ca_topic_score_gemma":0.04289431,"domain_scores_codex":[0.9998524,0.00002585693,0.00001696111,0.00004013035,0.00004452717,0.0000200301],"domain_scores_gemma":[0.9997703,0.00006837113,0.00002579425,0.00005335678,0.00005848371,0.00002368989],"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":[0.00003340714,0.00003103216,0.004310316,0.00006131514,0.00008418009,0.00008576446,0.0002305135,0.9442337,0.007215555,0.00609373,0.0008023176,0.03681812],"study_design_scores_gemma":[0.000008309657,0.000008082435,0.001068547,0.000009931026,0.00001604708,0.00002248601,0.00004157218,0.9893911,0.001496475,0.005349635,0.00257712,0.00001074717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05033623,0.0001901104,0.9366677,0.0001658472,0.00002960161,0.00006997636,0.001929147,0.004999941,0.005611466],"genre_scores_gemma":[0.5171099,0.0004238414,0.4750424,0.00003895407,0.00001450037,0.0001654437,0.00264621,0.0004672874,0.00409146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0234788,"threshold_uncertainty_score":0.04668427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01811309582808499,"score_gpt":0.1955745980307881,"score_spread":0.1774615022027031,"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."}}