{"id":"W4288689856","doi":"10.21203/rs.3.rs-1890673/v1","title":"Determination of concentration of heavy metals and metalloids in grapes grown in Gonabad vineyards and assessment of associated health risks","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Heavy Metals in Plants","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vice Chancellor for Research and Technology, Kerman University of Medical Sciences; Hospital for Sick Children","keywords":"Metalloid; Arsenic; Cadmium; Hazard quotient; Environmental chemistry; Chromium; Chemistry; Zinc; Health risk assessment; Manganese; Mean value; Toxicology; Animal science; Health risk; Heavy metals; Metal; Medicine; Environmental health; Mathematics; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.007076049,0.0002176978,0.00105725,0.0005517032,0.00005259597,0.00002359209,0.0002779635,0.000304345,0.0001840689],"category_scores_gemma":[0.001634921,0.0002322085,0.00009174782,0.0005021282,0.0002406196,0.0001070451,0.0007338291,0.001390464,7.369809e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006132681,"about_ca_system_score_gemma":0.001064029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004985451,"about_ca_topic_score_gemma":0.00109542,"domain_scores_codex":[0.994719,0.001559127,0.001239907,0.0005409366,0.001509169,0.0004318125],"domain_scores_gemma":[0.9973747,0.001060213,0.000690436,0.0003976728,0.0003670025,0.0001099948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003921702,0.002406606,0.7756642,0.03520038,0.0004946957,0.00005803079,0.004940502,0.0005193044,0.1386381,0.001269035,0.00004553326,0.04037145],"study_design_scores_gemma":[0.002730781,0.0006259648,0.8639085,0.003921136,0.00006362254,0.000005433213,0.002966658,0.01888471,0.1033806,0.002984894,0.00009011651,0.0004375744],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945244,0.002662897,0.00002482086,0.00012195,0.00004029863,0.0006883748,0.001084158,0.00001037456,0.0008426937],"genre_scores_gemma":[0.9941134,0.004349894,0.000814671,0.000003601153,0.00001091031,0.0001520611,0.0004926415,0.00002368712,0.00003916237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08824433,"threshold_uncertainty_score":0.946919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1302595304664363,"score_gpt":0.4798763028935511,"score_spread":0.3496167724271148,"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."}}