{"id":"W4292714700","doi":"10.1051/0004-6361/202141917","title":"ConKer: An algorithm for evaluating correlations of arbitrary order","year":2022,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; York University; National Energy Research Scientific Computing Center; Carnegie Mellon University; Office of Science; Johns Hopkins University; College of Engineering, Michigan State University; Harvard University; Ohio State University; National Science Foundation; University of Washington; Alfred P. Sloan Foundation; New Mexico State University; University of Portsmouth; Vanderbilt University; Yale University; University of Arizona; Princeton University; Brookhaven National Laboratory; U.S. Department of Energy","keywords":"Physics; Algorithm; Fast Fourier transform; Order (exchange); Context (archaeology); Grid; Galaxy; Astrophysics; Correlation function (quantum field theory); COSMIC cancer database; Scale (ratio); Correlation; Statistical physics; Computer science; Mathematics; Quantum mechanics","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":[0.002108524,0.001308983,0.0009927044,0.002032359,0.001066239,0.001850164,0.002191921,0.001147704,0.006172884],"category_scores_gemma":[0.01431904,0.0008041679,0.0008664647,0.002036614,0.001228087,0.003159683,0.003000086,0.001916404,0.002914659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222734,"about_ca_system_score_gemma":0.003173405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005803319,"about_ca_topic_score_gemma":0.009257914,"domain_scores_codex":[0.9978866,0.0003861013,0.0001789061,0.0003748512,0.000996204,0.0001773249],"domain_scores_gemma":[0.9940904,0.002527248,0.0005452323,0.001086096,0.001552366,0.0001985987],"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":[0.0005638957,0.0001696784,0.009778127,0.0003556779,0.0002126413,0.0003797905,0.0003418451,0.1206952,0.01105873,0.0681515,0.04520692,0.7430859],"study_design_scores_gemma":[0.00006943718,0.00005242138,0.001388429,0.00003028297,0.000023799,0.0002564467,0.00006285684,0.9345818,0.007340234,0.04116726,0.01498308,0.00004390978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004954765,0.0001697234,0.9864245,0.00008304648,0.00007373913,0.00007396901,0.0002152708,0.00625208,0.001752841],"genre_scores_gemma":[0.06705762,0.0001031481,0.9268283,0.0001479125,0.00006391531,0.0002271893,0.0009781491,0.001189862,0.003403923],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006172884,"threshold_uncertainty_score":0.02065039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123652647772773,"score_gpt":0.2413902544102616,"score_spread":0.2290249896329843,"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."}}