{"id":"W4399856365","doi":"10.1103/physrevd.109.123530","title":"Accurate kappa reconstruction algorithm for masked shear catalog","year":2024,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Kappa; Algorithm; Shear (geology); Computer science; Mathematics; Geology; Geometry","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005416723,0.0005438891,0.001290351,0.00008287089,0.0001943475,0.0002359406,0.001077489,0.00003812513,0.00001489475],"category_scores_gemma":[0.0004794567,0.0004189637,0.00101353,0.001367304,0.0001343672,0.001558243,0.0003560806,0.0005700754,0.00125925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001188781,"about_ca_system_score_gemma":0.0001448257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004243392,"about_ca_topic_score_gemma":2.564954e-7,"domain_scores_codex":[0.9964517,0.0002040822,0.0007403546,0.001302506,0.0005945117,0.0007068894],"domain_scores_gemma":[0.9974223,0.0006390275,0.0002257982,0.001112594,0.0002346917,0.0003655977],"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":[0.000001526466,0.0001198869,0.000002212772,0.003722585,0.00003296163,0.00000971927,0.00003138707,0.000002252647,0.001710511,0.02905772,0.00829189,0.9570174],"study_design_scores_gemma":[0.0002363012,0.0001761139,0.00003615124,0.01775111,0.0002216277,0.0000652305,0.000003329978,0.4903597,0.002551625,0.1079814,0.3798782,0.0007392048],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0009136233,0.1668586,0.8151883,0.009505488,0.00146213,0.002930401,0.0000795755,0.0009012675,0.002160688],"genre_scores_gemma":[0.03379918,0.6208492,0.3113933,0.02429282,0.005671065,0.002571838,0.000297477,0.0003297529,0.0007953842],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9562781,"threshold_uncertainty_score":0.9998262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02302563509882027,"score_gpt":0.4422616681728044,"score_spread":0.4192360330739842,"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."}}