{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001623062,0.0003616545,0.0002773259,0.00156492,0.0002266778,0.0005575136,0.0004588466,0.0004233311,0.0006385305],"category_scores_gemma":[0.003835461,0.000242778,0.0004382369,0.0006465375,0.0001580959,0.0004727575,0.0007836792,0.0002135399,0.0003061254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003378507,"about_ca_system_score_gemma":0.000224783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001904302,"about_ca_topic_score_gemma":0.002631748,"domain_scores_codex":[0.9991959,0.0001850606,0.00004158072,0.0002114698,0.0003067478,0.00005926828],"domain_scores_gemma":[0.9984915,0.0005732765,0.0002039556,0.0003718701,0.0002930459,0.00006634964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008005299,0.0002190886,0.4484278,0.0001474126,0.0003928544,0.0002007394,0.000195359,0.1018924,0.113918,0.001348709,0.001648156,0.3308089],"study_design_scores_gemma":[0.00003633753,0.0002884456,0.3871958,0.00001500723,0.0001375254,0.0004661791,0.00007272536,0.5459605,0.06216146,0.000841198,0.002781545,0.00004318804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8249088,0.0001581739,0.1707528,0.00007427807,0.000009950729,0.00005752741,0.0006110097,0.001724431,0.00170304],"genre_scores_gemma":[0.894346,0.00004176527,0.1041831,0.00002271072,0.000008090818,0.00002930734,0.0009021794,0.00006484606,0.0004019514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001904302,"threshold_uncertainty_score":0.008583665,"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."}}