{"id":"W3126316866","doi":"10.1093/mnras/stab653","title":"Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning","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":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"Science and Technology Facilities Council; National Aeronautics and Space Administration","keywords":"Physics; Astrophysics; Bimodality; Galaxy; Galaxy formation and evolution; Redshift; Galaxy cluster; Astronomy; Lenticular galaxy; Galaxy merger","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":[0.001183909,0.000204825,0.0004034546,0.001659568,0.0002721603,0.001192812,0.0004866206,0.0003585352,0.0006396841],"category_scores_gemma":[0.004167416,0.000217769,0.0003917647,0.001092219,0.000791372,0.0008035337,0.001000498,0.0003906696,0.0001662942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004756863,"about_ca_system_score_gemma":0.0001874391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00226705,"about_ca_topic_score_gemma":0.002565014,"domain_scores_codex":[0.9994444,0.0001836194,0.00003036854,0.0001688942,0.00008277833,0.00008985862],"domain_scores_gemma":[0.9969659,0.001379767,0.0007016293,0.0004544672,0.0002518707,0.0002463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003359237,0.0001351312,0.8955552,0.00006513295,0.0002844101,0.0001030759,0.0004458115,0.03442211,0.01878836,0.002797051,0.0005774649,0.04649035],"study_design_scores_gemma":[0.00001394503,0.00006885385,0.7302218,0.00001216676,0.00004240212,0.00007251321,0.0001987695,0.2585944,0.002173026,0.008147918,0.0004172165,0.0000369938],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882326,0.00008752623,0.01064275,0.00009151447,0.000003827348,0.000009650062,0.0001901503,0.0001051007,0.0006370224],"genre_scores_gemma":[0.9980654,0.00001253332,0.001643388,0.000008664789,0.000005625519,0.000003285867,0.000181558,0.000007561212,0.00007213771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00226705,"threshold_uncertainty_score":0.00626123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007872040319061453,"score_gpt":0.1983054645922222,"score_spread":0.1904334242731608,"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."}}