{"id":"W3042449007","doi":"10.1007/s10661-020-08484-y","title":"Seasonal variation of surface radiation and energy balances over two contrasting areas of the seasonally dry tropical forest (Caatinga) in the Brazilian semi-arid","year":2020,"lang":"en","type":"review","venue":"Environmental Monitoring and Assessment","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Seasonality; Arid; Environmental science; Tropical forest; Tropical and subtropical dry broadleaf forests; Dry season; Tropics; Atmospheric sciences; Geography; Hydrology (agriculture); Climatology; Ecology; Agroforestry; Biology; 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":[0.0001869785,0.0002091717,0.0003950509,0.00001513534,0.0001023586,0.00003243567,0.0001758883,0.00008494193,0.00001155235],"category_scores_gemma":[0.000009088671,0.0001359105,0.00008750425,0.000103104,0.0001170319,0.00008855648,0.0001722371,0.000262286,3.661514e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001932983,"about_ca_system_score_gemma":0.00002397159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001320679,"about_ca_topic_score_gemma":0.00002637098,"domain_scores_codex":[0.9985377,0.0002404554,0.0003683443,0.0002765001,0.0004258693,0.0001511371],"domain_scores_gemma":[0.9992419,0.0002210556,0.0003525313,0.0001354288,9.661844e-7,0.00004804967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003350436,0.00005842956,0.7954447,0.0001468387,0.00003588313,0.000002323085,0.0001363242,0.001622913,0.0001196199,0.0001359084,0.000001204789,0.2022925],"study_design_scores_gemma":[0.0002940306,0.00004543656,0.9571486,0.0007551002,0.0001510444,0.000009401155,0.00005066474,0.02550756,0.000007139224,0.00005912895,0.01580631,0.0001656378],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7302847,0.2678519,0.0003646341,0.00008502662,0.0002716137,0.0004838759,0.0002038678,0.00001068677,0.0004436855],"genre_scores_gemma":[0.7150083,0.2845824,0.000274283,0.000005300249,0.00005602006,0.00001573464,0.00003194956,0.00001045326,0.00001558645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2021269,"threshold_uncertainty_score":0.5542269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008380287140795369,"score_gpt":0.2553782175311472,"score_spread":0.2469979303903518,"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."}}