{"id":"W2130184138","doi":"10.1086/588518","title":"SiFTO: An Empirical Method for Fitting SN Ia Light Curves","year":2008,"lang":"en","type":"article","venue":"The Astrophysical Journal","topic":"Gamma-ray bursts and supernovae","field":"Physics and Astronomy","cited_by":249,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of Toronto","funders":"","keywords":"Photometry (optics); Light curve; Physics; Supernova; Astrophysics; Luminosity distance; Redshift; Wavelength; Generalization; Filter (signal processing); Optics; Computer science; Mathematics; Mathematical analysis; Galaxy; Stars; 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":[0.001577868,0.00130078,0.0006915521,0.003114956,0.0006725127,0.001120335,0.001774646,0.0008505135,0.009871957],"category_scores_gemma":[0.005697732,0.0005907135,0.001328859,0.002933064,0.0002642673,0.001245714,0.001246211,0.001169034,0.005866829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005674474,"about_ca_system_score_gemma":0.001361159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00645161,"about_ca_topic_score_gemma":0.0100751,"domain_scores_codex":[0.9994256,0.00008617902,0.00005685601,0.0001541256,0.0001887531,0.00008857214],"domain_scores_gemma":[0.9985545,0.0003320959,0.000183844,0.0003768731,0.0004730231,0.0000796707],"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":[0.001056647,0.0004828098,0.05317658,0.0005570005,0.0006467761,0.000297095,0.0005268673,0.06736702,0.02946009,0.007365273,0.0954666,0.7435972],"study_design_scores_gemma":[0.00019951,0.0001815342,0.02814481,0.00005607483,0.0001496359,0.0004409079,0.0001901124,0.8665517,0.0290724,0.006824437,0.06802884,0.0001600077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06095456,0.0001769834,0.8155316,0.0001093161,0.0002579169,0.0002738085,0.009684565,0.1084745,0.004536796],"genre_scores_gemma":[0.1502931,0.0001585881,0.8026367,0.0001076055,0.0000684324,0.0005021818,0.02305119,0.01594624,0.007236012],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009871957,"threshold_uncertainty_score":0.03302497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042216741529427,"score_gpt":0.3249891823364386,"score_spread":0.2945670149211443,"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."}}