{"id":"W4415633456","doi":"10.1051/0004-6361/202556854","title":"RIGEL: Feedback-regulated cloud-scale star formation efficiency in a simulated dwarf galaxy merger","year":2025,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Star formation; Galaxy; Dwarf galaxy; Galaxy merger; Galaxy formation and evolution; Molecular cloud; Stellar mass","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":[0.0003027716,0.0004866809,0.0006434522,0.0004490007,0.0005330116,0.0006580317,0.001105978,0.001138205,0.001767004],"category_scores_gemma":[0.001164681,0.0002807126,0.000687762,0.0003949243,0.0005714028,0.0004269331,0.0006306118,0.000808513,0.0001455498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008437447,"about_ca_system_score_gemma":0.0007693387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02587583,"about_ca_topic_score_gemma":0.01311336,"domain_scores_codex":[0.999889,0.00002747526,0.000005201089,0.00002062842,0.00001635162,0.00004130351],"domain_scores_gemma":[0.9994631,0.0002433999,0.00006766098,0.00003342766,0.0000575988,0.000134804],"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":[0.0003075446,0.0002215638,0.02085356,0.00005398119,0.0001014803,0.0003667622,0.0001384859,0.9695355,0.003588253,0.002107369,0.000846313,0.001879148],"study_design_scores_gemma":[0.00006893822,0.00006417317,0.002806161,0.000005219369,0.00001475337,0.00002378451,0.00004502019,0.9959091,0.0004303748,0.0003601358,0.0002614329,0.00001094795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935871,0.0001158816,0.002235715,0.0001702576,0.00003219079,0.00002395257,0.000600076,0.000228456,0.003006228],"genre_scores_gemma":[0.9967915,0.00004717507,0.002218341,0.0000602046,0.000008665862,0.0000258096,0.0004419385,0.00003282123,0.0003734787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02587583,"threshold_uncertainty_score":0.05145043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004104913134350271,"score_gpt":0.1987625507696011,"score_spread":0.1946576376352509,"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."}}