{"id":"W2603240302","doi":"","title":"Can a solid FeS layer help explain Mercury’s unique magnetic field?","year":2014,"lang":"en","type":"article","venue":"2014 AGU Fall Meeting","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mercury (programming language); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003661108,0.000137404,0.0001514436,0.00004868043,0.0001738925,0.00007748166,0.0001887169,0.00004072837,0.00008940566],"category_scores_gemma":[0.00002570128,0.0001247569,0.00004868976,0.0000790687,0.00002207257,0.0001840948,0.00003966244,0.0001298936,0.0004522262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008123807,"about_ca_system_score_gemma":0.00002865234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004562232,"about_ca_topic_score_gemma":0.001659906,"domain_scores_codex":[0.9990075,0.00009608253,0.0001909733,0.0002409799,0.0001482188,0.0003162994],"domain_scores_gemma":[0.9994622,0.0001250158,0.00008072671,0.0002036712,0.00003324951,0.00009513028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000454783,0.0001736257,0.6863341,0.00006429373,0.00006531503,0.000009764012,0.005918823,0.003774009,0.06147991,0.01913307,0.07863975,0.1443619],"study_design_scores_gemma":[0.005257604,0.00395449,0.06852565,0.001266018,0.0003676609,0.00003166432,0.01839782,0.2689243,0.1502898,0.09884195,0.3776135,0.006529411],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674888,0.00004879796,0.003132123,0.002063372,0.0002645767,0.0001476227,0.00001083751,0.00005920555,0.02678466],"genre_scores_gemma":[0.9975479,0.000005153408,0.0008242059,0.0004829453,0.0004454217,0.0000175285,0.0001083332,0.0000101277,0.0005584452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6178085,"threshold_uncertainty_score":0.689676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212759100173546,"score_gpt":0.2286308038909073,"score_spread":0.2165032128891718,"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."}}