{"id":"W1984518272","doi":"10.1088/0004-637x/783/1/29","title":"MOLECULAR OUTFLOWS DRIVEN BY LOW-MASS PROTOSTARS. I. CORRECTING FOR UNDERESTIMATES WHEN MEASURING OUTFLOW MASSES AND DYNAMICAL PROPERTIES","year":2014,"lang":"en","type":"article","venue":"The Astrophysical Journal","topic":"Astrophysics and Star Formation Studies","field":"Physics and Astronomy","cited_by":136,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"","keywords":"Outflow; Protostar; Astrophysics; Physics; Opacity; Excitation; Excited state; Kinetic energy; Dissociation (chemistry); Luminosity; Molecular cloud; Atomic physics; Star formation; Stars; 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":[0.00113043,0.0002195871,0.000294967,0.0009883107,0.0006156664,0.0008644019,0.0003450171,0.0003723878,0.0005359274],"category_scores_gemma":[0.003709575,0.0001670172,0.0001711932,0.0007624686,0.0002862661,0.0006960084,0.00073555,0.0002905717,0.0002489675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004552988,"about_ca_system_score_gemma":0.0003199384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004554998,"about_ca_topic_score_gemma":0.006755997,"domain_scores_codex":[0.9996336,0.00007125699,0.00003104514,0.0001116934,0.0001015828,0.00005088609],"domain_scores_gemma":[0.9986289,0.0002897913,0.0006617187,0.0001262609,0.0001990445,0.00009426196],"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":[0.0002664703,0.0000371667,0.9407622,0.00006268882,0.00004939336,0.0001097032,0.0002151578,0.001570462,0.02414339,0.0005197384,0.0004728588,0.03179079],"study_design_scores_gemma":[0.000008668369,0.00004724127,0.9744425,0.00002642474,0.00003897629,0.0001701962,0.0001882384,0.01327482,0.009382683,0.000624317,0.001784748,0.0000112759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989849,0.0007293486,0.006048021,0.0001612129,0.000043657,0.00002184556,0.0006893773,0.0001837574,0.002273702],"genre_scores_gemma":[0.9963837,0.0001588761,0.002367816,0.00003808483,0.00002613352,0.0000107298,0.0006213646,0.00001883833,0.0003745298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004554998,"threshold_uncertainty_score":0.009056926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531073628967066,"score_gpt":0.2219965970432401,"score_spread":0.2066858607535694,"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."}}