{"id":"W3087746226","doi":"10.5194/egusphere-egu2020-2407","title":"First direct monitoring and time-lapse mapping starts to reveal how a large submarine fan works","year":2020,"lang":"en","type":"article","venue":"","topic":"Geological formations and processes","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Canyon; Turbidity current; Submarine canyon; Geology; Seabed; Submarine pipeline; Oceanography; Coring; Submarine; Bathymetry; Sediment; Channel (broadcasting); Internal tide; Hydrology (agriculture); Geomorphology; Drilling; Internal wave; Structural basin; Sedimentary depositional environment; Geotechnical engineering","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":[0.0004507928,0.0008809529,0.0004383595,0.0008555533,0.0005746575,0.0009852148,0.000610327,0.0008172134,0.002912527],"category_scores_gemma":[0.0007088431,0.0002655104,0.0003048387,0.0006363134,0.0005268044,0.001144043,0.0007546832,0.001230701,0.001371878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006134593,"about_ca_system_score_gemma":0.0006241321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009857602,"about_ca_topic_score_gemma":0.02852703,"domain_scores_codex":[0.9996698,0.00002949525,0.000010143,0.0001133153,0.0001212197,0.00005611153],"domain_scores_gemma":[0.9993673,0.00008359299,0.00008417785,0.00008315076,0.0002694511,0.0001122678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002768233,0.000263676,0.1033422,0.0009813423,0.0001907258,0.001093788,0.001309559,0.002131627,0.6317437,0.002393811,0.01769365,0.2385791],"study_design_scores_gemma":[0.00003006949,0.0008788835,0.5832222,0.0005812146,0.0002625174,0.002301106,0.003537556,0.01609174,0.198407,0.003479695,0.1910561,0.0001519139],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.609571,0.008085158,0.2897605,0.003040117,0.001139927,0.0006338458,0.01239728,0.005806205,0.06956596],"genre_scores_gemma":[0.8534295,0.00355535,0.1203006,0.0009413247,0.0002673523,0.0004277699,0.005679998,0.0002922883,0.01510573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009857602,"threshold_uncertainty_score":0.01960045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02151469002722739,"score_gpt":0.1996893136689829,"score_spread":0.1781746236417555,"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."}}