{"id":"W4232068275","doi":"10.1515/iupac.81.0127","title":"Biomarker of Susceptibility","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Asthma and respiratory diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Environmental risk assessment; Computer science; Data science; Risk assessment; Ecology; Biology; Philosophy","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":[],"consensus_categories":[],"category_scores_codex":[0.001424307,0.001218747,0.001382508,0.003964367,0.0004712772,0.00195709,0.002002654,0.001679944,0.03858941],"category_scores_gemma":[0.01323212,0.0003342585,0.001700342,0.004413569,0.0003173744,0.001364261,0.001659698,0.002076616,0.02321805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001354468,"about_ca_system_score_gemma":0.001665633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01042894,"about_ca_topic_score_gemma":0.02143151,"domain_scores_codex":[0.9983248,0.000307364,0.0003441992,0.0005514755,0.0002920078,0.0001801375],"domain_scores_gemma":[0.9949422,0.001589359,0.001196638,0.0008789507,0.001089615,0.0003031586],"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":[0.0006442648,0.00009248152,0.06114563,0.004703986,0.0004733134,0.0001580226,0.00008767279,0.0009956042,0.0005072015,0.002500067,0.8987722,0.02991956],"study_design_scores_gemma":[0.0004547323,0.0001105726,0.121571,0.002242615,0.0004311544,0.0009278628,0.0002347125,0.001209897,0.0009009343,0.006955806,0.8648522,0.0001083847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001272683,0.0007975551,0.0002856682,0.000256466,0.00008669875,0.00003776425,0.9949955,0.0001247396,0.00214303],"genre_scores_gemma":[0.006094693,0.0006068131,0.001135821,0.0002919417,0.00005481386,0.0002018285,0.9897974,0.00004126863,0.001775531],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03858941,"threshold_uncertainty_score":0.1290945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941413077180673,"score_gpt":0.4155577661781124,"score_spread":0.3961436354063056,"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."}}