{"id":"W2311786951","doi":"10.1016/j.jqsrt.2016.03.017","title":"Retrieval of HCFC-142b (CH 3 CClF 2 ) from ground-based high-resolution infrared solar spectra: Atmospheric increase since 1989 and comparison with surface and satellite measurements","year":2016,"lang":"en","type":"article","venue":"Journal of Quantitative Spectroscopy and Radiative Transfer","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"National Oceanic and Atmospheric Administration; Université de Liège; Fédération Wallonie-Bruxelles; Fonds De La Recherche Scientifique - FNRS; National Aeronautics and Space Administration","keywords":"Environmental science; Troposphere; Satellite; Atmospheric sciences; Occultation; Altitude (triangle); Remote sensing; Physics; Geology; Astrophysics; Astronomy; Mathematics","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":[0.0005472725,0.0002791455,0.0006562771,0.00002131858,0.000174288,0.00005705983,0.0001037647,0.00008900822,0.0001648684],"category_scores_gemma":[0.00003448387,0.000169545,0.0000623204,0.0002694722,0.0005572196,0.0006315685,0.000004918333,0.0002248016,0.000003145901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002733135,"about_ca_system_score_gemma":0.0001420988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017007,"about_ca_topic_score_gemma":0.0007014048,"domain_scores_codex":[0.9980187,0.0003427883,0.0005616588,0.0002977786,0.0004724516,0.0003066417],"domain_scores_gemma":[0.9985645,0.0006245243,0.0003004595,0.00009767207,0.0001832024,0.0002296349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01119309,0.0001779588,0.9064526,0.00009283843,0.0005119704,0.00004658835,0.002284281,0.000621498,0.07609536,0.000323978,0.00001952681,0.002180333],"study_design_scores_gemma":[0.0050062,0.005055016,0.9461551,0.0003562821,0.0002893283,0.00001765902,0.001090192,0.002761364,0.03772936,0.001070668,0.0001238296,0.0003450315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9558719,0.009338875,0.03387415,0.0003025299,0.00007628996,0.0001963754,0.0001877036,0.000009027414,0.0001431532],"genre_scores_gemma":[0.9597835,0.003050481,0.03703989,0.00004651151,0.00004259796,2.185465e-7,0.00001276037,0.000009877276,0.00001417694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03970249,"threshold_uncertainty_score":0.6913846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0248123880512348,"score_gpt":0.2554773189989822,"score_spread":0.2306649309477475,"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."}}