{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002793416,0.0003098191,0.0004365979,0.00001415147,0.0004379916,0.0002005184,0.0008034979,0.0003488772,0.002282354],"category_scores_gemma":[0.0001557454,0.0001006327,0.0001807108,0.00007260606,0.00009415815,0.00006057549,0.0001554136,0.0003188723,0.00000700243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006317764,"about_ca_system_score_gemma":0.00007164132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002075378,"about_ca_topic_score_gemma":0.01132448,"domain_scores_codex":[0.9982773,0.00004864787,0.0002494833,0.0004427016,0.0006196979,0.0003621557],"domain_scores_gemma":[0.9991041,0.00005920424,0.0002678279,0.0002446954,0.0001753649,0.0001487452],"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":[0.00003976632,0.0000836376,0.00002162922,0.00002122728,0.00002604768,0.0001497952,5.740307e-7,1.110063e-7,0.00248206,9.798921e-7,0.9895075,0.007666703],"study_design_scores_gemma":[0.0001000651,0.000114372,0.001744875,0.0001414514,0.00004043281,0.0000210721,0.000006911923,8.987124e-7,0.00002803241,0.00003090451,0.9974467,0.0003243505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004499221,0.001109542,2.534532e-7,0.0004626496,0.0004635402,0.0001565592,0.9931778,0.0000405778,0.00008987918],"genre_scores_gemma":[0.0001131122,0.001158879,0.000009333887,0.0001943852,0.001366504,0.000006610382,0.9963319,0.000001172148,0.0008181202],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01111694,"threshold_uncertainty_score":0.9986297,"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."}}