{"id":"W4252729470","doi":"10.1515/iupac.79.1533","title":"Lesion","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; Computer science; Toxicology; Chemistry; Philosophy; Linguistics; Biology","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":[0.0001204836,0.000243606,0.0002287824,0.00001407093,0.00004545902,0.00001524115,0.0003403845,0.0002531856,0.03114487],"category_scores_gemma":[0.0001405225,0.0001833594,0.00008824418,0.00008466454,0.0001059905,0.00005209478,0.0002985737,0.000282224,0.00001974085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004636051,"about_ca_system_score_gemma":0.00002964601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003976778,"about_ca_topic_score_gemma":0.00003489322,"domain_scores_codex":[0.9985521,0.000007511374,0.0001999241,0.0003457809,0.0006226952,0.0002719727],"domain_scores_gemma":[0.9992869,0.00003087385,0.00006874868,0.0004560768,0.00001116256,0.000146175],"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":[0.00001613048,0.00004871737,0.000003999122,0.00003950536,0.000007837133,0.00002014385,0.00000124704,0.00001681301,0.003958693,2.022806e-7,0.9938317,0.002055014],"study_design_scores_gemma":[0.0002254115,0.00001835583,0.000008654973,0.0001204745,0.00002006409,0.000008507242,0.00000156708,0.000007974757,0.003511546,0.0000441827,0.9957684,0.0002648643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005256201,0.00006423405,0.00008811722,0.0001440939,0.0001598922,0.00005594412,0.9985106,0.00004697158,0.0004045296],"genre_scores_gemma":[0.000105708,0.0001886337,0.00003388127,0.00008480318,0.000347501,0.000004422569,0.9984405,0.00001720369,0.0007773303],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03112513,"threshold_uncertainty_score":0.9697408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008404936969294738,"score_gpt":0.3391892002194086,"score_spread":0.3307842632501138,"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."}}