{"id":"W2909512473","doi":"10.1016/j.envint.2018.12.055","title":"A comparative metagenomic and spectroscopic analysis of soils from an international point of entry between the US and Mexico","year":2019,"lang":"en","type":"article","venue":"Environment International","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Army Research Office; Division of Chemistry; Academy of Applied Science; National Institute on Minority Health and Health Disparities; University of Texas System; U.S. Department of Agriculture; University of Texas at El Paso; National Institutes of Health; National Science Foundation","keywords":"Soil water; Proteobacteria; Firmicutes; Environmental chemistry; Biology; Environmental science; Botany; Chemistry; Ecology; Bacteria; 16S ribosomal RNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016936,0.0002467346,0.0002076925,0.001437989,0.0005470156,0.0007281712,0.0001096249,0.0002686739,0.001272197],"category_scores_gemma":[0.0003261754,0.0001092116,0.000218672,0.001364314,0.0001452731,0.0001936614,0.0005301759,0.000198354,0.0001486701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000385657,"about_ca_system_score_gemma":0.0004018601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.027663,"about_ca_topic_score_gemma":0.03756617,"domain_scores_codex":[0.9998528,0.00001056716,0.00000810561,0.0000617351,0.00002411948,0.00004273656],"domain_scores_gemma":[0.9998701,0.00001520682,0.00003919589,0.000008328193,0.00004549388,0.00002166521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007108817,0.0001088194,0.6464193,0.0001138309,0.0002919092,0.0002100898,0.001163009,0.0002475515,0.3229482,0.000313296,0.0002970177,0.02717618],"study_design_scores_gemma":[0.000003414777,0.00006252096,0.9924188,0.000009944692,0.00005378286,0.0001142962,0.0007277313,0.0001822354,0.004662802,0.00003148372,0.001729151,0.000003864139],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954289,0.0002393879,0.0004324712,0.00003097447,0.000004910079,0.00001185403,0.002763627,0.000007858229,0.00108009],"genre_scores_gemma":[0.9928959,0.0003053918,0.001151831,0.00003030833,0.000003988629,0.00002276261,0.00445318,0.000005582815,0.001130997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.027663,"threshold_uncertainty_score":0.05500394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01214490692441435,"score_gpt":0.2571545412665601,"score_spread":0.2450096343421457,"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."}}