{"id":"W2995705012","doi":"10.3847/1538-3881/acd75c","title":"Automated SpectroPhotometric Image REDuction (ASPIRED)","year":2023,"lang":"en","type":"article","venue":"The Astronomical Journal","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Comisión Nacional de Investigación Científica y Tecnológica; National Science Foundation; Ministério da Ciência e Tecnologia; European Southern Observatory; Horizon 2020 Framework Programme; United States-Israel Binational Science Foundation; Canadian Institute for Advanced Research; Israel Science Foundation; Science and Technology Facilities Council; Instituto de Astrofísica de Canarias; Narodowe Centrum Nauki; European Commission; Liverpool John Moores University; Council for Higher Education","keywords":"Python (programming language); Data reduction; Reduction (mathematics); Workflow; Correctness; Automation; Software; Computer science; Data processing; Physics; Suite; Computational science; Algorithm; Data mining; Programming language; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002525482,0.001375407,0.001364316,0.003684795,0.001082089,0.002957198,0.00306043,0.0007475367,0.04295138],"category_scores_gemma":[0.004093605,0.001150711,0.002221255,0.002077639,0.0005802308,0.002589421,0.004199453,0.002664475,0.03242806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008413065,"about_ca_system_score_gemma":0.001769505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001651971,"about_ca_topic_score_gemma":0.002301423,"domain_scores_codex":[0.9977967,0.0001485352,0.0001703455,0.0005298021,0.001161707,0.0001929638],"domain_scores_gemma":[0.9982078,0.0002082589,0.000161032,0.0006362842,0.0006671318,0.0001196132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006051339,0.0002554119,0.007347326,0.001949518,0.0005330081,0.0003262295,0.0006389879,0.003422218,0.1225379,0.01033208,0.4776253,0.3744269],"study_design_scores_gemma":[0.0001585526,0.0001128325,0.01139362,0.0002488054,0.0001457729,0.0007428655,0.0002054418,0.04691767,0.2469984,0.01334634,0.6793211,0.0004085067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01358173,0.0005377972,0.5161346,0.0005112286,0.0005531828,0.0004562268,0.04704272,0.4065122,0.0146704],"genre_scores_gemma":[0.04752502,0.0004908032,0.7873789,0.0006439554,0.0001126625,0.00113231,0.08208565,0.06882785,0.01180287],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04295138,"threshold_uncertainty_score":0.1436867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01432423766284844,"score_gpt":0.2827219492661543,"score_spread":0.2683977116033059,"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."}}