{"id":"W4252310744","doi":"10.1515/iupac.87.0335","title":"Irwin Battery","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Chemistry; Linguistics; Philosophy; Data mining; Organic chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002103143,0.001589412,0.001836313,0.003428539,0.0008794001,0.003415193,0.003629019,0.00174376,0.199987],"category_scores_gemma":[0.01238647,0.0007905421,0.001496122,0.005336421,0.0004722438,0.002756286,0.002791408,0.002027029,0.3014967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00117632,"about_ca_system_score_gemma":0.002904593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008092398,"about_ca_topic_score_gemma":0.02005712,"domain_scores_codex":[0.9981849,0.0003340681,0.0003132532,0.0006188136,0.0003450721,0.0002038362],"domain_scores_gemma":[0.9957343,0.001116551,0.0003881403,0.001326295,0.001106731,0.0003279707],"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":[0.0001087391,0.00001707649,0.0007236893,0.0006893253,0.00002821846,0.00001640607,0.00001857297,0.0001336212,0.00005135429,0.0006109096,0.9920953,0.005506875],"study_design_scores_gemma":[0.0002167678,0.00001773022,0.001880415,0.0003579334,0.00002533041,0.0000440941,0.00005426233,0.0003078486,0.0002092529,0.002602817,0.9942591,0.00002440017],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001008891,0.00006921146,0.0001909733,0.0000932355,0.00003518509,0.00004997414,0.9959706,0.001194287,0.002295698],"genre_scores_gemma":[0.0005039667,0.0001168774,0.0008361876,0.0001810605,0.00002050531,0.0003215506,0.9952487,0.0003539099,0.002417328],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8000129,"threshold_uncertainty_score":0.6690233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317798299977891,"score_gpt":0.3833067799596037,"score_spread":0.3701287969598248,"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."}}