{"id":"W2883970575","doi":"10.48550/arxiv.1807.09820","title":"Cosmic String Wake Detection using 3D Ridgelet Transformations","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Astrophysics and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Wake; Cosmic string; String (physics); Computer science; Physics; Artificial intelligence; Theoretical physics; Mechanics","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":[0.0009607808,0.0003281513,0.0003787041,0.001535176,0.0003039771,0.001230214,0.0005086911,0.0004816121,0.001058873],"category_scores_gemma":[0.004027742,0.0002521384,0.0007184052,0.0008409899,0.0005645555,0.0006201675,0.001057094,0.0005005866,0.0001691182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003532299,"about_ca_system_score_gemma":0.0003342834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001649334,"about_ca_topic_score_gemma":0.001039849,"domain_scores_codex":[0.9996322,0.000163462,0.00001598793,0.00005708445,0.00007651905,0.00005472336],"domain_scores_gemma":[0.9974148,0.001144158,0.0006085598,0.0003797093,0.0001958588,0.0002568715],"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":[0.001313364,0.0002756678,0.2089486,0.0001431967,0.0004194397,0.001095242,0.0005084668,0.5858569,0.05094954,0.07796563,0.002373619,0.07015034],"study_design_scores_gemma":[0.00001753761,0.00003429717,0.01418506,0.0000053612,0.000007629749,0.00007330503,0.00002392092,0.9730279,0.002857014,0.009420238,0.000324601,0.00002305578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8976669,0.00007636998,0.09802836,0.0001508508,0.00002024856,0.0000255894,0.0006118564,0.000829997,0.002589836],"genre_scores_gemma":[0.9861485,0.00002873062,0.01325253,0.00001652457,0.00001102443,0.000009935041,0.0003610051,0.00003791498,0.0001337373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001649334,"threshold_uncertainty_score":0.005081177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04561728624657335,"score_gpt":0.1810482907952634,"score_spread":0.1354310045486901,"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."}}