{"id":"W4402408730","doi":"10.1103/physrevd.110.064028","title":"Differentiable and hardware-accelerated waveforms for gravitational wave data analysis","year":2024,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Pulsars and Gravitational Waves Research","field":"Physics and Astronomy","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"National Science Foundation","keywords":"Waveform; Gravitational wave; Computer science; Differentiable function; Physics; Astronomy; Telecommunications; Mathematics; Mathematical analysis","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":[0.0009968275,0.0007883388,0.0003109584,0.0007721603,0.0003183936,0.001432747,0.001445433,0.000645889,0.006531531],"category_scores_gemma":[0.005678937,0.0003884392,0.0004978086,0.0009820295,0.0005640099,0.001792229,0.0008566779,0.001563118,0.003185653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005244869,"about_ca_system_score_gemma":0.001050785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002017672,"about_ca_topic_score_gemma":0.002721519,"domain_scores_codex":[0.9995196,0.0001165862,0.00003777913,0.00006514351,0.0002266237,0.00003433909],"domain_scores_gemma":[0.9987746,0.0004914792,0.0001141187,0.000299306,0.0002745817,0.00004594254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000257756,0.000108822,0.002953679,0.0002369235,0.00005925477,0.0003319395,0.0003160241,0.2012608,0.04231636,0.2009139,0.01931961,0.5319249],"study_design_scores_gemma":[0.00002654228,0.00004429001,0.0003751161,0.00001748262,0.000007363753,0.00008755233,0.00002241494,0.9401375,0.01457333,0.03418346,0.01050561,0.00001925492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003938723,0.00003491278,0.9906631,0.0001274189,0.00002774653,0.00001962138,0.00009074817,0.003858466,0.001239357],"genre_scores_gemma":[0.06638286,0.0001089915,0.9297041,0.0001024004,0.0000324327,0.0000842765,0.0003611179,0.001066291,0.002157589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006531531,"threshold_uncertainty_score":0.02185017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0519343796423158,"score_gpt":0.4980142677371733,"score_spread":0.4460798880948575,"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."}}