{"id":"W4281396306","doi":"10.1029/2021gl097389","title":"Detailed Seafloor Imagery of Turbidity Current Bedforms Reveals New Insight Into Fine‐Scale Near‐Bed Processes","year":2022,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Geological formations and processes","field":"Earth and Planetary Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Geological Survey of Canada; Natural Resources Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l'Économie, de l’Innovation et des Exportations du Québec; Université Laval","keywords":"Turbidity current; Bedform; Turbidite; Geology; Bathymetry; Current (fluid); Seafloor spreading; Geomorphology; Outcrop; Erosion; Flume; Flow (mathematics); Sedimentary depositional environment; Oceanography; Sediment transport; Sediment; Geometry; Structural basin","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007349603,0.00017221,0.0003080364,0.0001592565,0.0008142235,0.0001280444,0.0006725787,0.00003774831,0.003560408],"category_scores_gemma":[0.0006002155,0.0001260457,0.0001064684,0.001670319,0.0004087876,0.000469457,0.0001996185,0.0008115105,0.0003243388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000202992,"about_ca_system_score_gemma":0.0004677692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002414615,"about_ca_topic_score_gemma":0.0006808732,"domain_scores_codex":[0.9969525,0.0003005732,0.0003704081,0.0003842165,0.001316758,0.0006755785],"domain_scores_gemma":[0.9983103,0.0007339042,0.0001058713,0.0003022585,0.0002363409,0.0003112854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001392785,0.001146502,0.5124044,0.003094952,0.0001405391,0.00009634731,0.01116408,0.008031779,0.01365059,0.0003624809,0.1261142,0.3224013],"study_design_scores_gemma":[0.001832894,0.002149451,0.811033,0.0001512759,0.00005324084,0.00002046754,0.001216143,0.004647634,0.00753996,0.0521438,0.1180138,0.00119836],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931154,0.0008266682,0.00009950521,0.004510905,0.0001669283,0.0003509594,0.00008956611,0.00004341154,0.0007966815],"genre_scores_gemma":[0.9983206,0.00004695482,0.0006103727,0.0003599884,0.0001950056,0.00002438321,0.0002341623,0.000005302147,0.0002032701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.321203,"threshold_uncertainty_score":0.9973505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04215502755472347,"score_gpt":0.2957816866847646,"score_spread":0.2536266591300412,"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."}}