{"id":"W3199735555","doi":"10.3847/1538-4357/ac35d6","title":"Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67","year":2022,"lang":"en","type":"preprint","venue":"The Astrophysical Journal","topic":"Gamma-ray bursts and supernovae","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Office of Science; University of Utah; Alfred P. Sloan Foundation; U.S. Department of Energy","keywords":"Physics; Principal component analysis; Astrophysics; Cluster (spacecraft); Spectral line; Stars; Open cluster; Curse of dimensionality; Artificial intelligence; Computer science; Astronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001827493,0.0005804656,0.0003819491,0.003228112,0.0006690084,0.0006066724,0.0006509176,0.0004613523,0.0007081247],"category_scores_gemma":[0.007473019,0.0002160067,0.0007886551,0.001308686,0.0007348603,0.0004969008,0.001056141,0.0005278672,0.0001332546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007785392,"about_ca_system_score_gemma":0.0006519436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01359745,"about_ca_topic_score_gemma":0.0102373,"domain_scores_codex":[0.9994674,0.0002717139,0.0000259672,0.00009962412,0.00009038101,0.00004478633],"domain_scores_gemma":[0.9965384,0.001965544,0.0004010698,0.0003865922,0.0004980302,0.000210474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007770397,0.0002297395,0.4159298,0.0003712373,0.0007010522,0.000567688,0.001516399,0.320561,0.02594592,0.01345124,0.002532535,0.2174163],"study_design_scores_gemma":[0.00001674249,0.00004136861,0.0792879,0.00001428496,0.00002835441,0.00007362301,0.0001931254,0.910797,0.001380552,0.007669751,0.0004619065,0.00003537119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8714059,0.0001777854,0.1261033,0.0003045965,0.000008987289,0.00003414082,0.0006013072,0.0005858216,0.0007781442],"genre_scores_gemma":[0.9657981,0.00003755844,0.03333661,0.00002118899,0.00001145992,0.00001867945,0.0006382226,0.0000498701,0.000088266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01359745,"threshold_uncertainty_score":0.02703661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05057186045149653,"score_gpt":0.3140717247376332,"score_spread":0.2634998642861367,"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."}}