{"id":"W4253429657","doi":"10.1515/iupac.85.0713","title":"Reverse Library Search","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Terminology; Chemical nomenclature; Mass spectrometry; Chemistry; Standardization; Analytical Chemistry (journal); Information retrieval; Computer science; Chromatography; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004551724,0.0003782256,0.000541505,0.0002872705,0.0001228199,0.0002805629,0.002749385,0.0003543858,0.001374695],"category_scores_gemma":[0.0002608051,0.0002632135,0.0001721526,0.0003413039,0.0001635454,0.0006649375,0.001398831,0.0004754556,0.00001915396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001101635,"about_ca_system_score_gemma":0.00133037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007778067,"about_ca_topic_score_gemma":0.00006863491,"domain_scores_codex":[0.9969844,0.0001489427,0.000381792,0.0007453858,0.001162079,0.0005773812],"domain_scores_gemma":[0.9973426,0.0002185537,0.0001412147,0.001933994,0.0001754258,0.0001881985],"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":[0.00002346043,0.0000739719,0.00001125442,0.00007773517,0.00003987423,0.0002960358,0.00001507574,3.815279e-7,0.000002014995,0.0003411487,0.9883324,0.01078663],"study_design_scores_gemma":[0.00041897,0.0001367741,0.00004545357,0.0002622154,0.00001818201,0.00003285625,0.00001312644,0.00003400877,0.00005609526,0.0008446975,0.9977666,0.0003710382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001577144,0.0008308602,0.00697111,0.005445081,0.00127757,0.0001896852,0.9847377,0.0003368139,0.0001954391],"genre_scores_gemma":[0.000004151816,0.001695976,0.002795158,0.001192316,0.000756613,0.000006721462,0.9920149,0.00002328489,0.001510884],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01041559,"threshold_uncertainty_score":0.999982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124198356732926,"score_gpt":0.3834491484996571,"score_spread":0.3622071649323278,"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."}}