{"id":"W7000607423","doi":"","title":"GEOQUÍMICA DO ARSÊNIO, DOS ELEMENTOS TERRAS RARAS E DOS METAIS PESADOS Cr, Zn, Ni e Pb NAS PLATAFORMAS CONTINENTAIS DO RIO DOCE (ES) E DE ABROLHOS (BA)","year":2018,"lang":"pt","type":"article","venue":"Americanae (AECID Library)","topic":"Geography and Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Université du Québec à Rimouski","keywords":"Erosion; Climate change; Heavy metals; Context (archaeology); Hydrology (agriculture)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","insufficient_payload"],"category_scores_codex":[0.0004986585,0.001752159,0.001644363,0.000427935,0.001701466,0.0004400787,0.002462212,0.000365412,0.0491089],"category_scores_gemma":[0.00006327574,0.001686857,0.0009128329,0.00205358,0.00470032,0.003423158,0.002608974,0.0009945341,0.00598547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004434875,"about_ca_system_score_gemma":0.00009786468,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03902031,"about_ca_topic_score_gemma":0.0005158197,"domain_scores_codex":[0.9905557,0.0004569349,0.001676903,0.002430864,0.001718537,0.003161069],"domain_scores_gemma":[0.9954441,0.0002319115,0.001071858,0.001915065,0.00002381651,0.001313317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003888614,0.0007678157,0.8454003,0.00005462522,0.000906021,0.0001250582,0.003080304,0.00007793218,0.00351552,0.0001404703,0.1178343,0.02770883],"study_design_scores_gemma":[0.002268884,0.00140274,0.769427,0.0001256666,0.0005188916,0.00005277603,0.004251053,0.0002110632,0.0112873,0.0001886688,0.2083072,0.001958774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726036,0.003171422,0.0006734154,0.003137231,0.001087256,0.001884132,0.0004791784,0.0004033759,0.01656035],"genre_scores_gemma":[0.9788197,0.004306929,0.003378494,0.004958025,0.0006317557,0.0003135795,0.0001557208,0.0002458564,0.007189965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09047288,"threshold_uncertainty_score":0.9995982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006863259811502148,"score_gpt":0.2119034723809267,"score_spread":0.2050402125694246,"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."}}