{"id":"W6968818694","doi":"10.5281/zenodo.5109803","title":"Making do Without Spectroscopy: Using Computational Models to Uncover Parameter Correlations in Binary Stars","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"","keywords":"Binary number; Markov chain Monte Carlo; Kepler; Observable; Binary star; Monte Carlo method; Stars; Markov process; Markov chain","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":[0.00196823,0.0007164805,0.001148254,0.00105449,0.001027801,0.002090202,0.001561237,0.001352265,0.0022094],"category_scores_gemma":[0.01082209,0.0007131691,0.001027904,0.0007444971,0.001425365,0.001948805,0.001222715,0.001336285,0.0002553453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156476,"about_ca_system_score_gemma":0.002023495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02100525,"about_ca_topic_score_gemma":0.01927512,"domain_scores_codex":[0.9997001,0.0001488743,0.0000130177,0.00005228318,0.00004252851,0.00004323274],"domain_scores_gemma":[0.9919562,0.006730306,0.0005472621,0.0003238187,0.0002246681,0.0002177062],"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":[0.00002935658,0.00002516878,0.00241349,0.00001281928,0.00001867419,0.00002481314,0.0000404219,0.9883642,0.00007460229,0.006827645,0.0001276574,0.002041089],"study_design_scores_gemma":[0.000004356378,0.000003499487,0.00009733975,0.000002602856,0.000002359538,0.000003285126,0.000005948118,0.9949477,0.00002351015,0.004836481,0.00007041757,0.000002492812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6719416,0.001019706,0.3103799,0.002456121,0.00009834181,0.0001519576,0.0009582532,0.0007664783,0.01222758],"genre_scores_gemma":[0.9261785,0.0003601637,0.07036093,0.0002181096,0.00006449675,0.0002437999,0.0005347241,0.0001313709,0.001907835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02100525,"threshold_uncertainty_score":0.04176593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07044994118310077,"score_gpt":0.2866536215037556,"score_spread":0.2162036803206548,"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."}}