{"id":"W2047744314","doi":"10.1007/s10661-014-3885-4","title":"Interspecific and locational differences in metal levels in edible fish tissue from Saudi Arabia","year":2014,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Agency for Toxic Substances and Disease Registry; National Research Council Canada; King Abdullah University of Science and Technology","keywords":"Mercury (programming language); Selenium; Arsenic; Environmental chemistry; Interspecific competition; Zinc; Ecotoxicology; Biology; Chemistry; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001302994,0.0001658059,0.0001242203,0.0005420431,0.0004850578,0.0003574326,0.0001711226,0.0001839618,0.0008146231],"category_scores_gemma":[0.0001918163,0.0001423911,0.0001544959,0.0003975533,0.0002595829,0.000135195,0.0003004126,0.0001778604,0.0001784432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000416202,"about_ca_system_score_gemma":0.000193434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03125614,"about_ca_topic_score_gemma":0.06568783,"domain_scores_codex":[0.9999098,0.00000773087,0.000009862533,0.0000351365,0.0000168099,0.000020643],"domain_scores_gemma":[0.9998314,0.00003315128,0.00004421459,0.00001131006,0.0000587951,0.00002111001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001080281,0.00007678699,0.6058673,0.00005499433,0.0001522055,0.0006762074,0.004272986,0.000293925,0.3746367,0.0001876133,0.0001179613,0.01258304],"study_design_scores_gemma":[0.000003228089,0.0001194503,0.9896543,0.000003918606,0.00004364433,0.0003172255,0.001352014,0.0001533899,0.007668495,0.00002246318,0.0006566782,0.000005184511],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997029,0.0000242701,0.00004152104,0.000003995418,9.227979e-7,7.723254e-7,0.00004976925,5.618047e-7,0.0001752546],"genre_scores_gemma":[0.9986287,0.00006055937,0.000134184,0.00001525789,0.000001095973,0.000002665248,0.0001452137,0.000001665847,0.00101065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03125614,"threshold_uncertainty_score":0.06214839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03005992261608437,"score_gpt":0.2832091633046072,"score_spread":0.2531492406885228,"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."}}