{"id":"W4250474520","doi":"10.1515/iupac.79.0833","title":"Antimetabolite","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Toxicology; Computer science; Library science; Chemistry; Philosophy; Biology; Linguistics","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":[0.0001428002,0.0002926198,0.0003151922,0.00001889667,0.0000449079,0.00002142659,0.0004063776,0.00025094,0.04389696],"category_scores_gemma":[0.0001552542,0.0002245984,0.0001163767,0.0001244709,0.0001419637,0.00006855981,0.0003094068,0.0003123586,0.00003308382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002874163,"about_ca_system_score_gemma":0.00003374035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004151456,"about_ca_topic_score_gemma":0.00001800058,"domain_scores_codex":[0.9983382,0.000009402961,0.0002419833,0.0003983621,0.0006642072,0.0003478375],"domain_scores_gemma":[0.9991432,0.00003109363,0.0000835771,0.0005523266,0.00001490783,0.0001748646],"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":[0.00001448721,0.00005484105,0.000007888641,0.00003900085,0.0000170086,0.00002187319,0.000001382712,0.00001300098,0.00309035,4.04998e-7,0.9950026,0.001737194],"study_design_scores_gemma":[0.0002580433,0.0000120145,0.00001943767,0.00008393158,0.00003614403,0.00001028703,0.000001118518,0.000007834985,0.003183123,0.00004248735,0.9960257,0.000319881],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004186083,0.0001665568,0.00007175229,0.0001146514,0.0001958722,0.00006384718,0.9981941,0.00004651867,0.000728096],"genre_scores_gemma":[0.0000641621,0.0003206133,0.00004799014,0.0001152205,0.000442842,0.000004622334,0.997815,0.00001904592,0.001170562],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04386387,"threshold_uncertainty_score":0.9569771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004894385718005453,"score_gpt":0.3215189275616619,"score_spread":0.3166245418436565,"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."}}