{"id":"W4250260972","doi":"10.1515/iupac.88.1400","title":"Teratogen","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Plant Pathogens and Resistance","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001466795,0.00126805,0.001423182,0.004089376,0.0007031967,0.002517391,0.002173212,0.001791572,0.1109501],"category_scores_gemma":[0.01113309,0.0005977699,0.001791457,0.005249518,0.0003424054,0.001837259,0.002192807,0.001751208,0.08233134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476851,"about_ca_system_score_gemma":0.003027203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01395358,"about_ca_topic_score_gemma":0.02660057,"domain_scores_codex":[0.9983546,0.0003066956,0.0004347855,0.0004125553,0.0003347586,0.0001566838],"domain_scores_gemma":[0.9950007,0.001626155,0.0008482269,0.001096144,0.00118246,0.0002463726],"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":[0.0002595036,0.00002855965,0.003753392,0.006493945,0.0001202678,0.00008307842,0.00005899418,0.0003465456,0.0003114578,0.001817674,0.9668364,0.01989023],"study_design_scores_gemma":[0.0001601846,0.00001728963,0.004729308,0.001590629,0.00007660218,0.0001421587,0.00005185952,0.0001279178,0.0001957559,0.001179891,0.991707,0.00002132683],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001506802,0.0004542049,0.000191582,0.000128049,0.00004618143,0.00003854844,0.9966319,0.0002369018,0.002121946],"genre_scores_gemma":[0.0007010305,0.0005969102,0.0007519106,0.0003101374,0.00002044726,0.0001898117,0.9956103,0.00009223427,0.001727201],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1109501,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01944545184403821,"score_gpt":0.3581091259368235,"score_spread":0.3386636740927853,"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."}}