{"id":"W4237731809","doi":"10.1515/iupac.87.0166","title":"Cramp","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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":[0.001260643,0.001685548,0.001294625,0.004206672,0.0009918223,0.003845522,0.002831038,0.001785572,0.1992592],"category_scores_gemma":[0.01146649,0.0007633461,0.001691476,0.007668908,0.0004087476,0.002924427,0.002825249,0.00176557,0.2604736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001554465,"about_ca_system_score_gemma":0.003141433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02372093,"about_ca_topic_score_gemma":0.05264592,"domain_scores_codex":[0.9983624,0.000268287,0.0002974689,0.0005056918,0.0003549673,0.0002112106],"domain_scores_gemma":[0.9956449,0.001131675,0.0004466381,0.001221243,0.001222097,0.0003333436],"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":[0.00008089933,0.000009874211,0.0007485348,0.0007413807,0.00002080446,0.00001201514,0.0000188642,0.00009684801,0.00003988083,0.0006159816,0.9929877,0.004627242],"study_design_scores_gemma":[0.0001164057,0.00001237202,0.001958372,0.0004379568,0.00001798708,0.00004448967,0.00005563585,0.000151646,0.0001245164,0.001289171,0.9957734,0.00001800496],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008432923,0.0001019991,0.00008622898,0.000101372,0.00003305199,0.00001665286,0.9970776,0.0005238216,0.001974998],"genre_scores_gemma":[0.0003226307,0.0001237029,0.0003379003,0.0001191292,0.00001183399,0.00007179235,0.9971042,0.0001717564,0.001736976],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8007408,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01722210917915114,"score_gpt":0.4300282269744537,"score_spread":0.4128061177953026,"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."}}