{"id":"W3009655588","doi":"10.1144/sp500-2019-196","title":"Mass wasting on Alpha Ridge in the Arctic Ocean: new insights from multibeam bathymetry and sub-bottom profiler data","year":2020,"lang":"en","type":"article","venue":"Geological Society London Special Publications","topic":"Geological Studies and Exploration","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Hydrographic Service; Geological Survey of Canada","funders":"","keywords":"Geology; Seafloor spreading; Bathymetry; Ridge; Escarpment; Debris; Arctic; Mass wasting; Mass movement; Seismology; Oceanography; Geomorphology; Paleontology; Landslide","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002509932,0.0001871787,0.0002320627,0.00001886429,0.0004858951,0.0002059797,0.0007146448,0.0001656836,0.001160775],"category_scores_gemma":[0.0008440819,0.0001111499,0.00007265996,0.0006956209,0.0002035396,0.0004016595,0.0001418593,0.0005114705,0.000225292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009747707,"about_ca_system_score_gemma":0.00003518324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001240644,"about_ca_topic_score_gemma":0.0008541213,"domain_scores_codex":[0.9981907,0.0001496348,0.0003234837,0.0006536128,0.0003444823,0.0003380867],"domain_scores_gemma":[0.9985434,0.0007543453,0.0001119688,0.0003338885,0.00005024901,0.0002061005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006644725,0.000131308,0.8718596,0.00001322163,0.00005030333,0.00000545226,0.002857094,0.0008001727,0.00004948894,0.00285559,0.1017798,0.01953159],"study_design_scores_gemma":[0.0004190473,0.0001643849,0.923961,0.000005915089,0.0000161877,8.577171e-7,0.001255896,0.01663532,0.000005745082,0.004573493,0.05278282,0.0001792955],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8843091,0.001260888,0.0008900922,0.1081903,0.000220787,0.0007029821,0.0003068602,0.0001218023,0.003997209],"genre_scores_gemma":[0.9855909,0.0005789601,0.002534148,0.006998364,0.002144779,0.000005153126,0.002109296,0.000002989198,0.0000353785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1012819,"threshold_uncertainty_score":0.9997523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0694325608996065,"score_gpt":0.2389779418394346,"score_spread":0.1695453809398281,"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."}}