{"id":"W4365137062","doi":"10.1093/mnras/stad1061","title":"Galaxy pairs in<scp>The Three Hundred</scp>simulations II: studying bound ones and identifying them via machine learning","year":2023,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ministerio de Ciencia e Innovación; Barcelona Supercomputing Center; Horizon 2020 Framework Programme; Science and Technology Facilities Council; European Commission; Comunidad de Madrid","keywords":"Physics; Galaxy; Astrophysics; RADIUS; Cluster (spacecraft); Upper and lower bounds; Mass fraction; Effective radius; Galaxy cluster; Computer science; Mathematical analysis","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":[0.001702177,0.0004924269,0.0009192598,0.0007470887,0.001039374,0.001283356,0.001892705,0.001177201,0.001955705],"category_scores_gemma":[0.005484359,0.0004521361,0.0009704091,0.0008035211,0.001466613,0.0008897586,0.001119672,0.001485333,0.0003079203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001070434,"about_ca_system_score_gemma":0.0008971517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01622445,"about_ca_topic_score_gemma":0.01482125,"domain_scores_codex":[0.9995197,0.0001754119,0.00001859759,0.00008291611,0.0000845469,0.0001188279],"domain_scores_gemma":[0.9967279,0.001389112,0.0002973492,0.0006272232,0.0003183478,0.0006399665],"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":[0.0007506046,0.000472119,0.1589255,0.0001145072,0.0005015568,0.000478407,0.0003081637,0.808755,0.002296953,0.01034819,0.01044544,0.006603519],"study_design_scores_gemma":[0.0001217384,0.00009945993,0.02889176,0.00002250343,0.00003449755,0.00006970319,0.0001704704,0.9636092,0.001313028,0.004303579,0.001326298,0.00003780261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936357,0.0000874415,0.002584121,0.0002570708,0.00002579821,0.00002268526,0.00121226,0.0003399375,0.001834998],"genre_scores_gemma":[0.993776,0.00002479722,0.002653632,0.0001058461,0.00001246802,0.00003777642,0.003049169,0.0001057643,0.0002347052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01622445,"threshold_uncertainty_score":0.03226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812957679044628,"score_gpt":0.2202953631224965,"score_spread":0.2021657863320502,"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."}}