{"id":"W2606382755","doi":"10.1103/physrevlett.118.161103","title":"Mass-Discrepancy Acceleration Relation: A Natural Outcome of Galaxy Formation in Cold Dark Matter Halos","year":2017,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"H2020 European Research Council; Partnership for Advanced Computing in Europe AISBL; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Durham University; Royal Society; British Infection Society; Science and Technology Facilities Council; European Commission","keywords":"Physics; Cold dark matter; Astrophysics; Dark matter; Acceleration; Hot dark matter; Galaxy; Dark matter halo; Galaxy formation and evolution; Astronomy; Scalar field dark matter; Dark fluid; Galaxy rotation curve; Baryon; Halo; Cosmology; Dark energy; Classical mechanics","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":[0.0006830104,0.0002837002,0.0002463,0.0007587626,0.0002595947,0.0007839182,0.0003896319,0.0003451625,0.0009665374],"category_scores_gemma":[0.003563829,0.0001399363,0.0003242188,0.0004418616,0.0008228057,0.000503879,0.0006946592,0.0004500785,0.00008756042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004517115,"about_ca_system_score_gemma":0.0002279233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003763901,"about_ca_topic_score_gemma":0.003243945,"domain_scores_codex":[0.9998466,0.0000463083,0.000007756005,0.00003240356,0.00002383861,0.0000430608],"domain_scores_gemma":[0.9988845,0.0004024527,0.0002541865,0.0001652169,0.00009220795,0.0002014145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007409054,0.0002215711,0.543487,0.0001466509,0.0003087617,0.0009365251,0.001022567,0.3592269,0.03466317,0.04253025,0.003786021,0.01292977],"study_design_scores_gemma":[0.0001595006,0.0002761833,0.3268801,0.00003486006,0.00006228147,0.0002824655,0.000409007,0.6382367,0.008928496,0.02352843,0.001149044,0.00005294842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978067,0.0000614283,0.001042658,0.00008562981,0.000003195634,0.000005729071,0.0001727732,0.00007231799,0.000749601],"genre_scores_gemma":[0.9992322,0.00002045624,0.0004604147,0.00001239964,0.000002967138,0.000003737315,0.0001582888,0.00001247312,0.00009710914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003763901,"threshold_uncertainty_score":0.007484019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829823486204053,"score_gpt":0.2806094440375743,"score_spread":0.2623112091755337,"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."}}