{"id":"W4240233037","doi":"10.1515/iupac.80.0220","title":"Summary and Recommendations","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Heavy Metal Exposure and Toxicity","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Lymphocyte; Beryllium; Cadmium; Immunology; Chemistry; Medicine; Metallurgy; Materials 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01197831,0.001342581,0.002130108,0.007100488,0.001375178,0.006387652,0.004190981,0.002986068,0.3415443],"category_scores_gemma":[0.1046609,0.0007041372,0.00388218,0.009976625,0.0005789403,0.006669196,0.003647042,0.003353046,0.1633223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003374197,"about_ca_system_score_gemma":0.01482826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01953415,"about_ca_topic_score_gemma":0.02267407,"domain_scores_codex":[0.9905876,0.003423495,0.002051008,0.001615653,0.001572142,0.0007501169],"domain_scores_gemma":[0.9569926,0.01341323,0.002819672,0.004330518,0.01925459,0.003189365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001347411,0.0000187698,0.001135235,0.003456761,0.0001154415,0.00002273343,0.00003840794,0.0001439137,0.00003305812,0.001693988,0.9602422,0.03296487],"study_design_scores_gemma":[0.0002163281,0.00002613444,0.003310672,0.009819805,0.0001601616,0.00005423911,0.0001915463,0.0001434963,0.0001007465,0.00516087,0.9807771,0.0000389164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005076222,0.00597734,0.002859054,0.02886537,0.005673855,0.001298846,0.9193602,0.001472047,0.0339857],"genre_scores_gemma":[0.004680241,0.01170047,0.01784764,0.0228935,0.002644316,0.006984383,0.8945513,0.001308282,0.03738992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3415443,"threshold_uncertainty_score":0.9392071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0141604020359365,"score_gpt":0.3703479953661528,"score_spread":0.3561875933302163,"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."}}