{"id":"W2489883178","doi":"10.3847/0004-637x/830/2/103","title":"STELLAR ATMOSPHERES, ATMOSPHERIC EXTENSION, AND FUNDAMENTAL PARAMETERS: WEIGHING STARS USING THE STELLAR MASS INDEX","year":2016,"lang":"en","type":"article","venue":"The Astrophysical Journal","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Theoretical Astrophysics; University of Toronto","funders":"","keywords":"Physics; Asteroseismology; Astrophysics; Angular diameter; Red supergiant; Stars; Stellar atmosphere; Supergiant; Stellar mass; Stellar evolution; Stellar mass loss; Stellar structure; Astronomy; RADIUS; Effective temperature; Giant star; Red giant; Binary star; Star formation","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":[0.000786702,0.0003544695,0.0003088217,0.001855571,0.0002197578,0.0006874393,0.0003092392,0.0003179125,0.0002769669],"category_scores_gemma":[0.002515576,0.0001960443,0.0002158971,0.0009763542,0.0003028723,0.0009845477,0.0006612435,0.000261413,0.0002335495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002240679,"about_ca_system_score_gemma":0.0001488554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001342885,"about_ca_topic_score_gemma":0.002331673,"domain_scores_codex":[0.999728,0.00008248876,0.00001411273,0.00008424061,0.00007675244,0.00001445115],"domain_scores_gemma":[0.9987749,0.0003992201,0.0003928797,0.0001766183,0.0001376259,0.0001187063],"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":[0.00009080453,0.00004565154,0.9273487,0.00003334283,0.000150037,0.00004422907,0.00009997771,0.01071699,0.02497011,0.0008493616,0.0002002244,0.03545069],"study_design_scores_gemma":[0.000008535018,0.00008713193,0.8040271,0.00001608374,0.00005925516,0.0001750506,0.00008964677,0.1789032,0.01380246,0.001959414,0.0008374462,0.00003474625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9617774,0.000345021,0.03608234,0.00003533662,0.000007488452,0.000009160558,0.0002080212,0.0001991792,0.001335992],"genre_scores_gemma":[0.9900398,0.00006374619,0.009632119,0.000006602029,0.00001038271,0.000002731156,0.000143035,0.00001273381,0.0000888626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001855571,"threshold_uncertainty_score":0.004160523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01558394578318795,"score_gpt":0.226512812274236,"score_spread":0.210928866491048,"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."}}