{"id":"W7014852682","doi":"","title":"Quality controlof selectedcosmeticsmarketed in Libya for traces oftoxicheavymetals: urgent need of guidelines harmonization","year":2023,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercury (programming language); Cadmium; Heavy metals; Cosmetics; Harmonization; Arsenic; Standardization","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004099055,0.0006099124,0.0008008197,0.002860313,0.002072323,0.00216782,0.000900868,0.0009984424,0.001672107],"category_scores_gemma":[0.002230855,0.0002690735,0.0004275728,0.002420077,0.001376112,0.0005878342,0.0009210364,0.0006631056,0.0005247191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031847,"about_ca_system_score_gemma":0.002738017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01145033,"about_ca_topic_score_gemma":0.01847182,"domain_scores_codex":[0.9939834,0.001343724,0.0005049573,0.0005882148,0.003331881,0.000247726],"domain_scores_gemma":[0.9973225,0.0002764562,0.000500663,0.0001853648,0.001635702,0.00007935385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008474498,0.0004119655,0.3320513,0.00406018,0.0002998167,0.001067137,0.00458535,0.001352194,0.2749139,0.001996143,0.005647656,0.3727669],"study_design_scores_gemma":[0.00008126601,0.001040236,0.570178,0.001859358,0.0003358234,0.002494674,0.007976778,0.004378499,0.274915,0.001887515,0.1346698,0.0001829945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351961,0.02443896,0.02043247,0.001708429,0.0004788467,0.0005354512,0.002269392,0.0003195073,0.01462094],"genre_scores_gemma":[0.9446532,0.008336382,0.03491795,0.001180026,0.0001253246,0.0003018004,0.002336225,0.0001278042,0.008021246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01145033,"threshold_uncertainty_score":0.02276736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02534028473073,"score_gpt":0.2642981570514835,"score_spread":0.2389578723207535,"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."}}