{"id":"W2328077890","doi":"10.5194/amt-9-3063-2016","title":"Instrumentation and measurement strategy for the NOAA SENEX aircraftcampaign as part of the Southeast Atmosphere Study 2013","year":2016,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Oceanic and Atmospheric Administration; National Aeronautics and Space Administration; California Institute of Technology; Purdue University; U.S. Environmental Protection Agency; National Science Foundation","keywords":"Environmental science; Meteorology; Atmosphere (unit); Aerosol; Daytime; Atmospheric sciences; Geography; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.001880775,0.0003200271,0.0002949959,7.234165e-7,0.0004242242,0.00006993473,0.0004983952,0.00009581102,0.0006624804],"category_scores_gemma":[0.0001544127,0.0001515733,0.0001346393,0.0002348253,0.0002513251,0.00020195,0.00004416923,0.0001163653,0.00001091227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000459406,"about_ca_system_score_gemma":0.0002031276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001370859,"about_ca_topic_score_gemma":0.001227857,"domain_scores_codex":[0.9971966,0.0001920156,0.0005432395,0.0004495797,0.001239643,0.0003788983],"domain_scores_gemma":[0.9984464,0.0001499225,0.0003534117,0.000578239,0.0003651603,0.0001068462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003870171,0.0003652626,0.4228515,0.0001328728,0.0004815405,0.000002401988,0.0007481964,0.0003799401,0.0184327,0.0001345732,0.004863102,0.5512209],"study_design_scores_gemma":[0.006130519,0.005575105,0.664099,0.001486679,0.001187344,0.00005704934,0.02076515,0.002692381,0.2198893,0.005686406,0.07008997,0.002341087],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971553,0.00222022,0.01425742,0.002236121,0.000465743,0.005568925,0.00006262994,0.0002925467,0.003343455],"genre_scores_gemma":[0.9968319,0.0001727312,0.002378236,0.0001188093,0.0001275698,0.0001295552,0.000002146414,0.00001407804,0.0002250016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5488798,"threshold_uncertainty_score":0.7253696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04146295444848624,"score_gpt":0.2366364888645402,"score_spread":0.1951735344160539,"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."}}