{"id":"W4241009763","doi":"10.1515/iupac.79.1449","title":"Idiosyncrasy","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Linguistics and Cultural Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Linguistics; Philosophy; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001785454,0.0003890195,0.0005260038,0.00006833694,0.0004600698,0.0002216376,0.0003385713,0.000124959,0.02327908],"category_scores_gemma":[0.0004047951,0.0002258599,0.0001845289,0.0000205243,0.0003373234,0.00004837765,0.0001690818,0.0002695464,0.0000195418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001508144,"about_ca_system_score_gemma":0.0001432782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003526797,"about_ca_topic_score_gemma":0.007571582,"domain_scores_codex":[0.9982173,0.0000281625,0.0003601662,0.0003448989,0.0006883728,0.0003610697],"domain_scores_gemma":[0.9984441,0.00005417641,0.0001913601,0.0003926653,0.0008244651,0.00009317453],"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":[0.00002390885,0.00006456485,4.441287e-7,0.00008386714,0.0001599975,0.00003301808,0.0002748128,2.57409e-8,2.807099e-7,0.003534182,0.9945896,0.001235314],"study_design_scores_gemma":[0.0003017975,0.0001172066,0.000001191403,0.0002528849,0.0001296218,0.000001932155,0.0002342125,1.646324e-7,0.000001235291,0.001271666,0.997285,0.0004031016],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001059827,0.00165879,0.000001373569,0.000645377,0.003014898,0.0001404604,0.989026,0.00007103566,0.005431466],"genre_scores_gemma":[0.00004172255,0.001454673,0.0000033846,0.0003963473,0.01054375,0.00001109521,0.977088,0.00002673296,0.01043431],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02325954,"threshold_uncertainty_score":0.9776137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703466676095004,"score_gpt":0.3681106902036783,"score_spread":0.3410760234427282,"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."}}