{"id":"W1984311762","doi":"10.1117/12.930614","title":"Highly validated atmospheric water vapor vertical profiles using Raman lidar technique","year":2012,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Lidar; Water vapor; Environmental science; Remote sensing; Raman spectroscopy; Atmospheric model; Atmospheric sciences; Materials science; Meteorology; Geology; Optics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002897221,0.0003377467,0.0001911499,0.000414544,0.0003522337,0.0002664898,0.0004860251,0.0003301621,0.0004725769],"category_scores_gemma":[0.0002619842,0.00017815,0.0002369493,0.0004224303,0.0001584779,0.0003580164,0.0004064541,0.0004057126,0.000211615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002090066,"about_ca_system_score_gemma":0.0003438413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00461395,"about_ca_topic_score_gemma":0.009126617,"domain_scores_codex":[0.9997041,0.00002900234,0.00000833044,0.00007512298,0.0001533684,0.0000300656],"domain_scores_gemma":[0.999853,0.00002318151,0.00002178856,0.00001758095,0.00007466801,0.000009743389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008970553,0.0000868651,0.02192287,0.00005931146,0.00004536816,0.00009336326,0.0001662705,0.003239996,0.9497727,0.0003264393,0.0003198066,0.02387725],"study_design_scores_gemma":[0.00005428653,0.0004428927,0.1004739,0.0000257809,0.00006865444,0.0002134351,0.0002411162,0.05581786,0.8375507,0.0004067923,0.004621412,0.00008305121],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776058,0.0001718191,0.0177409,0.00003590841,0.00001876274,0.00004155359,0.0009614996,0.0005621144,0.002861727],"genre_scores_gemma":[0.9760988,0.0001047637,0.02243093,0.00002779301,0.000009161822,0.00003110381,0.0007716287,0.00003848691,0.0004873489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00461395,"threshold_uncertainty_score":0.009174168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201452957832011,"score_gpt":0.2367067602494674,"score_spread":0.2246922306711472,"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."}}