{"id":"W4225105014","doi":"10.1109/mlke55170.2022.00058","title":"Classification of Quasars, Galaxies, and Stars by Using XGBoost in SDSS-DR16","year":2022,"lang":"en","type":"article","venue":"","topic":"Gamma-ray bursts and supernovae","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Hyperparameter; Boosting (machine learning); Computer science; Stars; Artificial intelligence; Hyperparameter optimization; Naive Bayes classifier; Quasar; Sky; Gradient boosting; Galaxy; Machine learning; Test data; Astrophysics; Physics; Support vector machine; Computer vision; Random forest","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":[0.001555143,0.001012638,0.0007708398,0.002032775,0.0004351498,0.0007386503,0.001116914,0.0007958494,0.001116647],"category_scores_gemma":[0.00113063,0.000293574,0.0008418201,0.001688768,0.0002705542,0.0005227036,0.0005727696,0.0007095385,0.001314298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007444439,"about_ca_system_score_gemma":0.0005520218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01146741,"about_ca_topic_score_gemma":0.007964082,"domain_scores_codex":[0.9992217,0.0001557913,0.00006082402,0.0001898809,0.0002566606,0.0001150461],"domain_scores_gemma":[0.9997461,0.00004783266,0.00003032321,0.0000531564,0.00009548909,0.00002715525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001265523,0.001260499,0.06096468,0.0003795153,0.0004411692,0.0002077267,0.000236847,0.1834181,0.01514862,0.002129427,0.06143594,0.673112],"study_design_scores_gemma":[0.0001610369,0.0003525533,0.04102874,0.00005197806,0.00005539857,0.0000946724,0.0001683073,0.9105495,0.02245965,0.002568951,0.02245434,0.00005481784],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7897789,0.001526277,0.1560647,0.0005429361,0.000469847,0.0006770986,0.01667338,0.02744383,0.00682319],"genre_scores_gemma":[0.653331,0.0003602015,0.2880255,0.0002528214,0.00007667654,0.0004261122,0.0496613,0.0007548835,0.007111322],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01146741,"threshold_uncertainty_score":0.02280128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02142645906473362,"score_gpt":0.2471657339514638,"score_spread":0.2257392748867302,"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."}}