{"id":"W1857693140","doi":"10.1093/mnrasl/slv101","title":"Detection of two power-law tails in the probability distribution functions of massive GMCs","year":2015,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society Letters","topic":"Astrophysics and Star Formation Studies","field":"Physics and Astronomy","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"Science and Technology Facilities Council; Agence Nationale de la Recherche; Deutsche Forschungsgemeinschaft","keywords":"Physics; Astrophysics; Log-normal distribution; Power law; Star formation; Gravitational collapse; Molecular cloud; Mass distribution; Extinction (optical mineralogy); Probability density function; Stars; Range (aeronautics); Galaxy; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002825115,0.0001213189,0.0002343789,0.000006662791,0.0000961113,0.00001382228,0.0002441554,0.00002406714,0.000006554854],"category_scores_gemma":[0.000008435932,0.00007838558,0.0003360976,0.0001170026,0.000357907,0.000109224,0.0001051507,0.0001744085,0.000001603189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000073094,"about_ca_system_score_gemma":0.00002509796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00106379,"about_ca_topic_score_gemma":0.00002325762,"domain_scores_codex":[0.9989854,0.0001018173,0.0003991023,0.0001315938,0.0002135845,0.0001685731],"domain_scores_gemma":[0.9991584,0.00008627003,0.0003932823,0.0002411012,0.00009109115,0.00002984776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00008285746,0.0003762737,0.07661903,0.00002358805,0.0002096082,1.555205e-8,0.002549784,0.9145359,0.0008870621,0.003226991,0.0007964292,0.0006924024],"study_design_scores_gemma":[0.005865796,0.0006749448,0.7373386,0.0001321458,0.0005551135,2.531958e-8,0.03219661,0.1941178,0.02215594,0.004502101,0.001717246,0.0007437161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990669,0.000008765858,0.007560924,0.000901824,0.0001108083,0.0002579552,0.0002425356,0.000003963863,0.0002442739],"genre_scores_gemma":[0.9994386,8.975157e-9,0.000419976,0.00002629093,0.00005802762,0.0000206521,0.00002710141,0.000004723109,0.000004556352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7204182,"threshold_uncertainty_score":0.3196471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01055548086418407,"score_gpt":0.2116603301366076,"score_spread":0.2011048492724235,"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."}}