{"id":"W4318906289","doi":"10.48550/arxiv.2301.13484","title":"CELEBI: The CRAFT Effortless Localisation and Enhanced Burst Inspection Pipeline","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Pulsars and Gravitational Waves Research","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Government of Western Australia; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Swinburne University of Technology; Australian Government; Commonwealth Scientific and Industrial Research Organisation; Science and Industry Endowment Fund","keywords":"Software; Computer science; Python (programming language); Pipeline (software); Real-time computing; Pathfinder; Computer hardware; Artificial intelligence; Acoustics; Physics; Operating system","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":[0.00139271,0.001571986,0.0009895576,0.001756832,0.0006385405,0.001912955,0.002909045,0.0007829104,0.03176476],"category_scores_gemma":[0.005121765,0.001231471,0.001319897,0.00117395,0.0007504781,0.001754002,0.002882967,0.002733923,0.03242816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061225,"about_ca_system_score_gemma":0.00242436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009472496,"about_ca_topic_score_gemma":0.007544791,"domain_scores_codex":[0.9991252,0.00007563305,0.00004967175,0.0002384376,0.000387872,0.0001231303],"domain_scores_gemma":[0.9987287,0.0002518453,0.00009849772,0.0003489437,0.0004586586,0.000113416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009438138,0.0001226769,0.007204146,0.0006478378,0.0002284674,0.0003554135,0.000715909,0.01246939,0.02422026,0.01101426,0.6759439,0.2661339],"study_design_scores_gemma":[0.0005545193,0.0001814752,0.01525293,0.0002228472,0.0001192185,0.0005600529,0.0002096472,0.3190109,0.06957937,0.03351568,0.5604246,0.0003687158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.004690735,0.0001707005,0.2914025,0.0002268337,0.0001249143,0.0001482562,0.009621821,0.6856539,0.007960348],"genre_scores_gemma":[0.110675,0.0004638552,0.5698247,0.001038492,0.000168432,0.00109161,0.08447247,0.2093025,0.02296303],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03176476,"threshold_uncertainty_score":0.1062638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0630966256716558,"score_gpt":0.2477732417051201,"score_spread":0.1846766160334643,"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."}}