{"id":"W3136788368","doi":"10.1093/mnras/stab719","title":"Classifying stars, galaxies, and AGNs in CLAUDS + HSC-SSP using gradient boosted decision trees","year":2021,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"National Astronomical Observatories, Chinese Academy of Sciences; Natural Sciences and Engineering Research Council of Canada; Ministry of Finance; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Japan Science and Technology Corporation","keywords":"Physics; Astrophysics; Galaxy; Active galactic nucleus; Redshift; Photometry (optics); Binary number; Stars; Extrapolation; Astronomy; Statistics","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":[0.002607282,0.001220684,0.00105049,0.002168035,0.0007193657,0.001418724,0.002642315,0.001554738,0.002026883],"category_scores_gemma":[0.003730876,0.0004202269,0.001422718,0.001333929,0.0006138395,0.000891554,0.001705046,0.001845019,0.002086718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317662,"about_ca_system_score_gemma":0.001031295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02462806,"about_ca_topic_score_gemma":0.04177881,"domain_scores_codex":[0.999123,0.000226647,0.00005244941,0.000250219,0.0001863139,0.0001614311],"domain_scores_gemma":[0.998005,0.0006373384,0.0001538457,0.0003423521,0.0005168575,0.0003447047],"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":[0.001809304,0.001336153,0.2587987,0.0003488728,0.0007293017,0.000478813,0.0003411749,0.4085797,0.008432732,0.002112259,0.05738046,0.2596525],"study_design_scores_gemma":[0.00009905954,0.0001093132,0.01585858,0.00002729778,0.00005108946,0.00007174087,0.0001504219,0.9748901,0.002994639,0.002570339,0.003152916,0.00002451112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8943586,0.0007537943,0.07234576,0.0009146538,0.0001167877,0.0002702447,0.01460865,0.01217904,0.004452471],"genre_scores_gemma":[0.8506349,0.00008383705,0.09005712,0.0005644713,0.00008000391,0.0001118217,0.05412184,0.0003602489,0.003985729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02462806,"threshold_uncertainty_score":0.04896945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01233703478333681,"score_gpt":0.2166813963830126,"score_spread":0.2043443615996758,"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."}}