{"id":"W7100874145","doi":"","title":"Preprint typeset using L ATEX style emulateapj v. 6/22/04 GEMINI SPECTROSCOPY OF SUPERNOVAE FROM SNLS: IMPROVING HIGH REDSHIFT SN SELECTION AND CLASSIFICATION","year":2008,"lang":"en","type":"article","venue":"","topic":"Gamma-ray bursts and supernovae","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Redshift; Galaxy; Supernova; Dark energy; Telescope; Selection (genetic algorithm)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001400743,0.003107612,0.002411818,0.006262601,0.001088256,0.008749642,0.002830661,0.00191129,0.7463975],"category_scores_gemma":[0.00566335,0.0013439,0.00295207,0.004875182,0.0006844303,0.003542138,0.00515688,0.002435589,0.711254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107469,"about_ca_system_score_gemma":0.0008714703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002425871,"about_ca_topic_score_gemma":0.003435729,"domain_scores_codex":[0.998805,0.0001087494,0.0001088611,0.0002784201,0.0005239646,0.0001749572],"domain_scores_gemma":[0.9975443,0.0003222124,0.0001886232,0.001225303,0.0004181055,0.0003013811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002953309,0.0001192075,0.002812951,0.000824429,0.0001894861,0.0003500547,0.0001206401,0.001104549,0.004134037,0.003513673,0.92286,0.06367567],"study_design_scores_gemma":[0.0002233137,0.0001045625,0.01063455,0.0003245855,0.00008975614,0.0005331376,0.00009493918,0.004891802,0.007534185,0.00796425,0.9675024,0.000102669],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.007486416,0.0008149773,0.05154659,0.002183902,0.00452022,0.000423887,0.3797343,0.3362964,0.2169933],"genre_scores_gemma":[0.02712351,0.001379731,0.04149513,0.0006880069,0.001966566,0.0003742798,0.5457659,0.1474016,0.2338053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7463975,"threshold_uncertainty_score":0.3617331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02307925574468285,"score_gpt":0.2501515377069774,"score_spread":0.2270722819622946,"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."}}