{"id":"W6891778777","doi":"10.48550/arxiv.1902.08161","title":"Galaxy shape measurement with convolutional neural networks","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Ground truth; Galaxy; Deep learning; Gaussian; Sky; Weak gravitational lensing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005953015,0.001364105,0.000399196,0.0009845757,0.0002310134,0.0007255403,0.001322003,0.0007479695,0.002022235],"category_scores_gemma":[0.002837725,0.0004039021,0.0006448704,0.0009693519,0.0003290159,0.000991537,0.0009353804,0.0005745041,0.001332125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001554276,"about_ca_system_score_gemma":0.0004820192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02116111,"about_ca_topic_score_gemma":0.02425049,"domain_scores_codex":[0.9996216,0.00004885305,0.00001279318,0.0001433898,0.000111659,0.00006163906],"domain_scores_gemma":[0.9991758,0.0001990495,0.0001071588,0.0002534382,0.0002018619,0.00006258576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003514264,0.0001214421,0.05106427,0.00009508845,0.0002158692,0.0001145904,0.00006450792,0.7220268,0.01405058,0.001594433,0.007099073,0.2032018],"study_design_scores_gemma":[0.00000602793,0.0000233033,0.005360821,0.000005086475,0.000008030923,0.0000178095,0.000009441152,0.9887533,0.004375895,0.000832196,0.0005989184,0.000009143264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7958661,0.0007464966,0.1713337,0.0004819738,0.000133289,0.0001115496,0.006957062,0.01614782,0.00822196],"genre_scores_gemma":[0.9420997,0.0001098524,0.04693422,0.000148658,0.00003204834,0.00004627014,0.008018904,0.0002549142,0.002355452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02116111,"threshold_uncertainty_score":0.04207587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06769357096857338,"score_gpt":0.1621543078506796,"score_spread":0.09446073688210625,"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."}}