{"meta":{"query_hash":"179e02223b33","filters":{"venue":"Revista de Engenharia e Tecnologia"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/179e02223b33","api":"https://metacan.xera.ac/api/v1/cohort?venue=Revista+de+Engenharia+e+Tecnologia"},"results":[{"id":"W2173492578","doi":"","title":"PREVISOR SVR-LSSVR WAVELET NA PROJEÇÃO DE SÉRIES TEMPORAIS","year":2015,"lang":"pt","type":"article","venue":"Revista de Engenharia e Tecnologia","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Support vector machine; Wavelet; Humanities; Artificial intelligence; Computer science; Philosophy","score_opus":0.06713114773101062,"score_gpt":0.33141165712343024,"score_spread":0.26428050939241965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2173492578","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008957175,0.0044233976,0.9779114,0.0038567905,0.0001845005,0.0014605036,0.00007458014,0.0012710779,0.0018605521],"genre_scores_gemma":[0.6126468,0.00040170658,0.3825616,0.000755912,0.0003093318,0.00054095755,0.000057915047,0.00007741356,0.0026483417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99600405,0.00038539578,0.0008893586,0.0011417946,0.0005473598,0.0010320233],"domain_scores_gemma":[0.9965474,0.00029961066,0.0005743326,0.0015165198,0.0005414463,0.0005206649],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014819424,0.00058442034,0.00064919377,0.00022412834,0.00035915212,0.00083481,0.002189443,0.00044052754,0.00006984745],"category_scores_gemma":[0.00085411343,0.0005688751,0.00023689847,0.0012625406,0.00025311342,0.00054109463,0.0009007634,0.0007916445,0.00037244105],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006482415,0.0005603959,0.001165799,0.0004395379,0.00021358792,0.00016995792,0.0029188872,0.0006431921,0.0015676427,0.8658529,0.0511864,0.07521689],"study_design_scores_gemma":[0.0017253568,0.0014578841,0.0028096142,0.0009345005,0.00028266202,0.0007910169,0.00082330033,0.15909867,0.00561812,0.11264319,0.7108776,0.0029380776],"about_ca_topic_score_codex":0.000041671577,"about_ca_topic_score_gemma":0.000001927154,"teacher_disagreement_score":0.7532097,"about_ca_system_score_codex":0.0006733735,"about_ca_system_score_gemma":0.0013941822,"threshold_uncertainty_score":0.9996763},"labels":[],"label_agreement":null}]}