{"id":"W4392670092","doi":"10.57209/e-locucao.v1i20.420","title":"SUSTENTABILIDADE DE DATA CENTERS COM O USO DA TI-VERDE","year":2021,"lang":"pt","type":"article","venue":"Revista Científica e-Locução","topic":"Green IT and Sustainability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Cape verde; Geography; Political science; Sociology; Ethnology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001393855,0.0007759885,0.001019901,0.0001860179,0.0003892198,0.0009687424,0.001993729,0.0003922253,0.001941188],"category_scores_gemma":[0.0009647966,0.000881599,0.0004350194,0.00128856,0.0002304721,0.0005318078,0.001706015,0.00100748,0.0003839927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001371968,"about_ca_system_score_gemma":0.0006905516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009933767,"about_ca_topic_score_gemma":0.00008813792,"domain_scores_codex":[0.9940162,0.0005138924,0.001174289,0.001670711,0.0008247538,0.001800125],"domain_scores_gemma":[0.9936258,0.0002797824,0.000192523,0.004732898,0.0003867455,0.0007822085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004940715,0.005086125,0.4634951,0.02978737,0.002639884,0.006009421,0.01341936,0.007873146,0.01353165,0.02603827,0.3856251,0.04600056],"study_design_scores_gemma":[0.001970486,0.0001079329,0.02603016,0.0006912455,0.000627924,0.0001863553,0.00717987,0.07179614,0.0007594027,0.00006474242,0.8889287,0.001657056],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9243401,0.02525827,0.02410506,0.006423385,0.003804761,0.002593395,0.003020545,0.001099901,0.009354641],"genre_scores_gemma":[0.9875004,0.0005652634,0.0005515607,0.0002859934,0.0003367933,0.00002100317,0.001242184,0.0001723312,0.009324474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5033036,"threshold_uncertainty_score":0.9993635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03556317903038129,"score_gpt":0.2811778436142333,"score_spread":0.245614664583852,"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."}}