{"id":"W3160669121","doi":"10.1002/essoar.10507013.1","title":"Sediments in sea ice drive the Canada Basin surface Mn maximum: insights from an Arctic Mn ocean model","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of British Columbia","funders":"University of British Columbia Graduate School; Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Arctic; Preprint; The arctic; Sea ice; Oceanography; World Wide Web; Geology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002634078,0.0006745292,0.0004432996,0.0004525341,0.001022856,0.001220404,0.001167897,0.001084499,0.001780002],"category_scores_gemma":[0.0009197907,0.0004000621,0.0008199434,0.0004896407,0.0006560264,0.0003352172,0.0007450552,0.0006787349,0.0001394721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004666524,"about_ca_system_score_gemma":0.007030576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.833604,"about_ca_topic_score_gemma":0.7179506,"domain_scores_codex":[0.9999143,0.00001635255,0.000003660028,0.00001832573,0.00001335041,0.00003394109],"domain_scores_gemma":[0.9997085,0.00007839582,0.00003368657,0.00001183082,0.00008689958,0.0000807063],"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":[0.00005919217,0.00003239723,0.01804949,0.00001733151,0.0000423385,0.00009225926,0.00004054666,0.9782894,0.0007364445,0.001237607,0.000546439,0.0008565693],"study_design_scores_gemma":[0.00003548472,0.00001653195,0.005312791,0.000008033712,0.00002985988,0.000007380548,0.00007239766,0.9936044,0.0001228327,0.0002567741,0.0005204465,0.00001305216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858953,0.0002226696,0.002553697,0.0006071462,0.00003424134,0.00002591499,0.001610406,0.00009462201,0.008955919],"genre_scores_gemma":[0.9954219,0.0001672175,0.001549978,0.00009110456,0.00001182385,0.00001992359,0.001043693,0.00003696189,0.001657363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.166396,"threshold_uncertainty_score":0.3347518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191008322763366,"score_gpt":0.202444024707857,"score_spread":0.1905339414802233,"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."}}