{"id":"W4229865974","doi":"10.1515/iupac.79.1168","title":"Dose–Response Relationship","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Computer science; Multidisciplinary approach; Toxicology; Chemistry; Biology; Philosophy; Linguistics; Sociology; Social 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":[],"consensus_categories":[],"category_scores_codex":[0.003038502,0.002006639,0.002402794,0.003350328,0.0004077984,0.002298575,0.002737937,0.002053796,0.08346366],"category_scores_gemma":[0.02323888,0.0006314504,0.004978891,0.003911606,0.0003563031,0.00168493,0.001065865,0.002257957,0.05108966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001564045,"about_ca_system_score_gemma":0.001847517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006817594,"about_ca_topic_score_gemma":0.01131564,"domain_scores_codex":[0.9960884,0.000721329,0.0007587273,0.001587145,0.0006510011,0.0001934469],"domain_scores_gemma":[0.9920494,0.004520997,0.0009606719,0.001252879,0.001057771,0.0001584073],"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":[0.001504873,0.0002586198,0.03476114,0.008615351,0.002432521,0.0001394845,0.00005304007,0.004487126,0.000713904,0.002238331,0.890546,0.05424959],"study_design_scores_gemma":[0.001420707,0.0003697872,0.04829243,0.001562252,0.00214436,0.001049014,0.00007479905,0.004180099,0.001367977,0.007046645,0.9323359,0.0001560306],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001237368,0.001758134,0.0008713741,0.0002915467,0.0001603233,0.0001091147,0.9926449,0.0004288622,0.002498234],"genre_scores_gemma":[0.01412263,0.001772627,0.002466036,0.001060709,0.0001697785,0.0007286583,0.9740768,0.0002235839,0.005379193],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08346366,"threshold_uncertainty_score":0.2792138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04502577651846953,"score_gpt":0.4442013327098705,"score_spread":0.399175556191401,"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."}}