{"id":"W2898174255","doi":"","title":"Orbital Resonances and GPU Acceleration of Binary Black Hole Inspiral Simulations","year":2018,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Black Holes and Theoretical Physics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Government of Ontario; Compute Canada","keywords":"Acceleration; Physics; Binary number; Black hole (networking); Binary black hole; Astrophysics; Computer science; Classical mechanics; Gravitational wave","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005730414,0.0005649813,0.0004124423,0.0003429712,0.0003810702,0.0009744169,0.001245467,0.0005391969,0.003933311],"category_scores_gemma":[0.002304777,0.0002299823,0.0003841234,0.0004708109,0.0004367686,0.0006507619,0.0007163215,0.0008827249,0.0006934091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006205373,"about_ca_system_score_gemma":0.0007743738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007229255,"about_ca_topic_score_gemma":0.00702604,"domain_scores_codex":[0.9997075,0.00009427059,0.0000131067,0.0000352653,0.0001035113,0.00004619266],"domain_scores_gemma":[0.9994574,0.0002390464,0.00002915768,0.00008718918,0.0001280085,0.0000591688],"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":[0.001005112,0.0003322842,0.01551727,0.0003710676,0.0001676624,0.0005272882,0.001054095,0.7686695,0.02887561,0.05535111,0.0190626,0.1090664],"study_design_scores_gemma":[0.0000370648,0.00003125885,0.0005221582,0.0000109796,0.000008253382,0.00001272107,0.00004032677,0.9890164,0.003673397,0.002778134,0.003862759,0.000006500378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7222146,0.0009402073,0.1917433,0.00121142,0.0004928373,0.0001775632,0.001097227,0.01390456,0.06821831],"genre_scores_gemma":[0.8703908,0.000236156,0.1219716,0.0001538274,0.00002890345,0.0001050547,0.0007871506,0.0009961188,0.005330398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007229255,"threshold_uncertainty_score":0.01437438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01469438372446083,"score_gpt":0.3103522585077713,"score_spread":0.2956578747833105,"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."}}