{"id":"W3138029272","doi":"10.1051/0004-6361/202040106","title":"Fragmentation and kinematics in high-mass star formation","year":2021,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Astrophysics and Star Formation Studies","field":"Physics and Astronomy","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Centre National de la Recherche Scientifique; Science and Technology Facilities Council; Deutsche Forschungsgemeinschaft; Max-Planck-Gesellschaft; Consejo Nacional de Ciencia y Tecnología","keywords":"Physics; Astrophysics; Star formation; Fragmentation (computing); Protein filament; Molecular cloud; Millimeter; Kinematics; Context (archaeology); Stars; Classical mechanics; Chemistry","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":[0.0001952859,0.0001568541,0.0001442241,0.0005064346,0.0002229036,0.0004423892,0.0002243781,0.0002140204,0.0007493915],"category_scores_gemma":[0.0006457951,0.0001385961,0.0001591315,0.0005566226,0.0003972862,0.0002773709,0.0003115842,0.0001976272,0.0001694006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004051711,"about_ca_system_score_gemma":0.0001135719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002954067,"about_ca_topic_score_gemma":0.002522956,"domain_scores_codex":[0.9999362,0.00001068387,0.000004170578,0.0000186642,0.00001512532,0.00001513684],"domain_scores_gemma":[0.9995973,0.00004196507,0.0002345084,0.00002760364,0.00004049957,0.0000581465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002013723,0.00002996989,0.9398039,0.00005695769,0.00005376931,0.000431208,0.0006693499,0.002604929,0.04223935,0.000805492,0.0001146161,0.01298902],"study_design_scores_gemma":[0.000002654428,0.00002217868,0.9972096,0.00000452778,0.000006273862,0.0002978424,0.00009711186,0.0007666197,0.0009294655,0.0004570046,0.0002042723,0.000002496246],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998442,0.0003303569,0.0005216522,0.00001486238,0.000001747432,0.000002449894,0.00004601296,0.000009596606,0.0006313262],"genre_scores_gemma":[0.9994164,0.00007921943,0.0002909151,0.000003946925,0.000002046525,0.000001162433,0.00009318435,0.00000204713,0.0001111231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002954067,"threshold_uncertainty_score":0.00587374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006735385218861465,"score_gpt":0.2135176348485709,"score_spread":0.2067822496297095,"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."}}