{"id":"W4229588177","doi":"10.1515/iupac.85.0466","title":"Forward Library Search","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Chemical nomenclature; Terminology; Mass spectrometry; Chemistry; Standardization; Information retrieval; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; Linguistics; 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":[0.0006172952,0.0003531186,0.0004294259,0.0004356468,0.000187432,0.0005057466,0.00240807,0.0003258209,0.002428759],"category_scores_gemma":[0.0001289714,0.0002433734,0.0002025298,0.0005299107,0.0001174902,0.00150798,0.001238868,0.0006313517,0.00004344065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001763069,"about_ca_system_score_gemma":0.001862535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002207915,"about_ca_topic_score_gemma":0.0000102168,"domain_scores_codex":[0.9961355,0.0001102414,0.0005169254,0.0004679578,0.002127243,0.0006420889],"domain_scores_gemma":[0.9976365,0.0001113512,0.0001521751,0.001339147,0.0004234421,0.0003373845],"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":[0.00003151358,0.00007092307,0.000004538696,0.00007514323,0.00002052643,0.00006533751,0.00002365748,5.29022e-7,0.000001308593,0.0005900111,0.9757445,0.02337195],"study_design_scores_gemma":[0.000483265,0.0002114797,0.00003210533,0.0001380511,0.00001167217,0.00001909849,0.000006587635,0.0001412304,0.0001055591,0.000214479,0.9982869,0.0003495831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003529855,0.0001254409,0.01190038,0.00236365,0.000710824,0.0003156967,0.9841345,0.0002349898,0.0001792422],"genre_scores_gemma":[0.000005467565,0.0005441245,0.0009490442,0.0007654367,0.0004703282,0.0000122991,0.9951994,0.0000197859,0.002034127],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02302237,"threshold_uncertainty_score":0.9984832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951267440733798,"score_gpt":0.3882767175633903,"score_spread":0.3687640431560523,"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."}}