{"id":"W4383046455","doi":"10.48550/arxiv.2306.17333","title":"Rubin Observatory LSST Stars Milky Way and Local Volume Star Clusters Roadmap","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Medical Research Council; Magyar Tudományos Akadémia; Nuclear Safety and Security Commission; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Institute for Theoretical Astrophysics; Agencia Nacional de Investigación y Desarrollo; National Aeronautics and Space Administration; Vetenskapsrådet; National Science Foundation","keywords":"Milky Way; Physics; Stars; Star cluster; Observatory; Sky; Astronomy; Star (game theory); Astrophysics; Globular cluster; Cluster (spacecraft); Galaxy; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004008732,0.0007997192,0.001017885,0.005276236,0.002094351,0.005069153,0.00256513,0.001397051,0.07704604],"category_scores_gemma":[0.00653942,0.0005939875,0.0007501685,0.004959428,0.0005877455,0.004607577,0.005649527,0.002072589,0.04196423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002369994,"about_ca_system_score_gemma":0.008003176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06599163,"about_ca_topic_score_gemma":0.0361726,"domain_scores_codex":[0.9981871,0.0002098069,0.00007290338,0.0003928931,0.0007023102,0.0004349063],"domain_scores_gemma":[0.9935291,0.0005967755,0.0005204508,0.00120074,0.001798789,0.002354066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001690965,0.0000515961,0.005872749,0.0001921333,0.0000169692,0.00006009074,0.0001291047,0.0004686001,0.0001768643,0.01752767,0.9196327,0.05570238],"study_design_scores_gemma":[0.00005952773,0.00002542831,0.01174197,0.00008792855,0.0000101886,0.00003785361,0.0001082527,0.0004122947,0.000190518,0.00733012,0.9799707,0.00002512576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01664999,0.005538868,0.01170362,0.02657366,0.002238897,0.001022876,0.5657574,0.02026257,0.3502522],"genre_scores_gemma":[0.04676413,0.003928489,0.03840378,0.00300889,0.001091089,0.001217074,0.752866,0.004377328,0.1483432],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07704604,"threshold_uncertainty_score":0.2577447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05651287831752427,"score_gpt":0.1806551475404107,"score_spread":0.1241422692228864,"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."}}