{"id":"W2516810781","doi":"","title":"Mercury’s Internal Magnetic Field: Results from MESSENGER’s Low-altitude Campaign","year":2014,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mercury (programming language); Environmental science; Meteorology; Physics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004136588,0.0004228588,0.0004906478,0.0006247153,0.0007749189,0.0006261425,0.0004181137,0.0006548951,0.001607624],"category_scores_gemma":[0.0007958903,0.0001799084,0.0003086645,0.001032507,0.0003831431,0.000391172,0.001111701,0.0006441987,0.0007755932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009501218,"about_ca_system_score_gemma":0.0007891497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04774874,"about_ca_topic_score_gemma":0.07918873,"domain_scores_codex":[0.999707,0.00002952226,0.000005477134,0.00005586698,0.0001032292,0.00009890196],"domain_scores_gemma":[0.9994414,0.00006373346,0.0001408281,0.00008285208,0.0001192164,0.0001518665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004197473,0.000881335,0.8262242,0.0003485208,0.0007225103,0.001563362,0.005376525,0.004622893,0.03905389,0.001316123,0.04886709,0.06682607],"study_design_scores_gemma":[0.0001712995,0.0001663365,0.9852896,0.00001654909,0.000165439,0.0000634913,0.0003550416,0.00100553,0.002530107,0.0001543877,0.01005384,0.00002832121],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876778,0.00007596983,0.000202428,0.0005507673,0.00002744898,0.00001463232,0.004390578,0.0001802685,0.006880204],"genre_scores_gemma":[0.991471,0.00006281776,0.0003510095,0.0001517413,0.00006939388,0.00001882945,0.006088994,0.00008680946,0.001699466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04774874,"threshold_uncertainty_score":0.09494162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01139536122238726,"score_gpt":0.2245432613183745,"score_spread":0.2131479000959873,"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."}}