{"id":"W2069687740","doi":"10.1097/ftd.0b013e3181db99a8","title":"Hair Methylmercury: A New Indication for Therapeutic Monitoring","year":2010,"lang":"en","type":"article","venue":"Therapeutic Drug Monitoring","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Western University","funders":"","keywords":"Methylmercury; Therapeutic drug monitoring; Mercury (programming language); Medicine; MERCURY EXPOSURE; Adverse effect; Hair analysis; Intensive care medicine; Toxicology; Drug; Environmental health; Obstetrics; Pharmacology; Environmental chemistry; Biology; Chemistry; Pathology; Bioaccumulation; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005102162,0.0002617209,0.0002328593,0.00006946574,0.0004078385,0.00008539019,0.0003527436,0.00009514351,0.0002598763],"category_scores_gemma":[0.00003660916,0.0002362282,0.0001134295,0.0002790132,0.0001189222,0.0003751328,0.00009023568,0.000304185,0.0002313328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001031661,"about_ca_system_score_gemma":0.00003478686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002003662,"about_ca_topic_score_gemma":0.00001578727,"domain_scores_codex":[0.9984082,0.00004659097,0.0002973707,0.0003699627,0.0003843596,0.0004935273],"domain_scores_gemma":[0.9989901,0.0002253576,0.0001559411,0.0003987646,0.00002191807,0.0002079104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003059363,0.00004971241,0.2343122,0.00001115303,0.00008871958,4.611797e-7,0.005083508,0.00003116989,0.4018813,0.0002432535,0.0003070906,0.3579609],"study_design_scores_gemma":[0.001228609,0.00008900662,0.4482665,0.00004720328,0.0001777637,0.000007831456,0.002052174,0.0001572509,0.4823301,0.009845374,0.0550711,0.000727069],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887971,0.0007122877,0.003248936,0.001123714,0.00329044,0.0006048313,0.000003361447,0.0002174968,0.00200183],"genre_scores_gemma":[0.9926141,0.0001280356,0.003880153,0.00009522483,0.001201237,0.0001293057,0.000002495001,0.00004810931,0.001901332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3572338,"threshold_uncertainty_score":0.9633104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03729835702344095,"score_gpt":0.3175545463889526,"score_spread":0.2802561893655117,"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."}}