{"id":"W2614400323","doi":"10.3847/1538-4357/aa72dd","title":"Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter","year":2017,"lang":"en","type":"article","venue":"The Astrophysical Journal","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Université de Montréal; Western University; Canadian Institute for Theoretical Astrophysics; Herzberg Institute of Astrophysics; University of Toronto","funders":"","keywords":"Exoplanet; Planet; False positive paradox; Matched filter; Physics; Sensitivity (control systems); Astrophysics; False positive rate; Stars; Computer science; Point spread function; Light curve; Algorithm; Filter (signal processing); Artificial intelligence; Optics; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004018407,0.000162562,0.0002784999,0.00001073,0.0008359956,0.0002660809,0.0002291881,0.00002073296,0.0000104453],"category_scores_gemma":[0.00002160106,0.00007813599,0.00005215842,0.00001713695,0.0002895719,0.0001701192,0.0001469156,0.0003858006,0.000002190392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006464542,"about_ca_system_score_gemma":0.00005218315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009641215,"about_ca_topic_score_gemma":0.00004846305,"domain_scores_codex":[0.9990354,0.000192779,0.0001593414,0.0001346323,0.0002351241,0.000242792],"domain_scores_gemma":[0.9987984,0.0003343444,0.0003958663,0.0003535501,0.00005312367,0.00006467143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001313379,0.00004785358,0.9860855,0.000008082381,0.0001898368,0.000006187767,0.0002814922,0.001524608,0.001797097,0.00009456243,0.0002648605,0.009568576],"study_design_scores_gemma":[0.0004518742,0.00004746266,0.9748377,0.00003369419,0.0001021021,0.00004495436,0.0001146099,0.02354782,0.0003084932,0.0003985263,0.000006523936,0.0001062241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821368,0.0000118802,0.01660751,0.0001892711,0.00009312772,0.0000865195,0.00007231414,0.000003955728,0.0007985489],"genre_scores_gemma":[0.9986916,0.000001904677,0.0008419883,0.00002353435,0.0003623813,9.994047e-7,0.0000112387,0.00001146865,0.00005494064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02202322,"threshold_uncertainty_score":0.6429887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002848394498426,"score_gpt":0.2374058554894823,"score_spread":0.217377371544498,"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."}}