{"id":"W4296538553","doi":"10.1002/esp.5482","title":"Linking uplift, erosion, and sedimentation using landscape evolution models: Madagascar since the Late Cretaceous","year":2022,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Networks Canada Society; University of Victoria","funders":"","keywords":"Geology; Cretaceous; Erosion; Cenozoic; Structural basin; Paleontology; Terrigenous sediment; Submarine pipeline; Denudation; Continental margin; Geologic time scale; Sea level; Physical geography; Oceanography; Tectonics; Geography","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":[0.0005267859,0.0001161936,0.0001363612,0.00004290205,0.001293545,0.00007408329,0.0001153185,0.0000563845,0.0002130973],"category_scores_gemma":[0.00001583952,0.00007392716,0.00001672018,0.000247237,0.000120583,0.0002914251,0.00005566719,0.0002739963,0.000006956916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000120916,"about_ca_system_score_gemma":0.00008430642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003057404,"about_ca_topic_score_gemma":0.001519341,"domain_scores_codex":[0.9990283,0.00009017558,0.0001461055,0.0002156574,0.0002229972,0.0002967342],"domain_scores_gemma":[0.9995499,0.0001640636,0.00007491601,0.00009402854,0.00004945405,0.00006769825],"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":[0.00007383696,0.000005917906,0.9128509,0.00006332813,0.00001097378,0.000005183729,0.0007932535,0.08588992,0.00001447331,0.00003868789,0.000007686072,0.0002458816],"study_design_scores_gemma":[0.0007390762,0.0002646416,0.3977345,0.00003282898,0.00004174602,0.0003642893,0.002956337,0.5914738,0.00006947081,0.005303353,0.0007412887,0.0002786615],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854461,0.01297364,0.0003693954,0.0005651504,0.00009145649,0.0001857586,0.00002896939,0.00002981739,0.0003097032],"genre_scores_gemma":[0.9987336,0.0005652461,0.0002456247,0.0001349127,0.00002147383,0.000002181646,0.00008148104,0.000003571433,0.0002118966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5151163,"threshold_uncertainty_score":0.994903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02111273536269792,"score_gpt":0.2321640841868411,"score_spread":0.2110513488241432,"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."}}