{"id":"W6929467390","doi":"10.48550/arxiv.1810.05238","title":"Impact of Accretion Flow Dynamics on Gas-dynamical Black Hole Mass Estimates","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Ion Transport and Channel Regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"","keywords":"Supermassive black hole; Black hole (networking); Galaxy; Accretion (finance); Stellar kinematics; Stellar dynamics; Intermediate-mass black hole; Spin-flip","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000803811,0.0002695826,0.0002417778,0.0001097962,0.00004404324,0.00001398628,0.0002982653,0.0005377951,0.00007707108],"category_scores_gemma":[0.00001578577,0.0002825169,0.0003570345,0.0001142592,0.0002191749,0.000005748806,0.0001242542,0.0001904588,0.00002297733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001309998,"about_ca_system_score_gemma":0.00009227102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004637198,"about_ca_topic_score_gemma":0.00004223084,"domain_scores_codex":[0.998922,0.00003732992,0.0001710813,0.0005783985,0.00006944544,0.0002216815],"domain_scores_gemma":[0.9990019,0.000009636603,0.0001882009,0.0005222812,0.0001862213,0.00009182611],"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":[0.0007365249,0.0001568272,0.02241866,0.0001018192,0.0002730626,0.00001922269,0.00003017668,0.9583398,0.01670011,0.0007575695,0.0002593794,0.0002069122],"study_design_scores_gemma":[0.0005749092,0.0006151946,0.02219114,0.00009460791,0.000134055,9.055984e-7,0.0000287444,0.9620481,0.01062069,0.003291508,0.00001821672,0.0003819444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9130787,0.00001098952,0.08556664,0.00001326424,0.0001903801,0.0001707958,0.0001732561,0.0000215267,0.0007744627],"genre_scores_gemma":[0.9964789,0.0001151459,0.000250182,0.000007108638,0.0001470788,3.950577e-7,0.002584495,0.00002872571,0.0003879353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08531646,"threshold_uncertainty_score":0.9999627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0242767196394725,"score_gpt":0.2042508298984281,"score_spread":0.1799741102589556,"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."}}