{"id":"W4238719185","doi":"10.1515/iupac.78.0386","title":"Lag Phase","year":2016,"lang":"no","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Pesticide; Computer science; Units of measurement; Relation (database); Data science; Management science; Ecology; Engineering; Chemistry; Data mining; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.001447926,0.001861767,0.001480041,0.005070358,0.001093774,0.003068076,0.002635181,0.001638728,0.165989],"category_scores_gemma":[0.01342445,0.0006786218,0.001982381,0.007624165,0.0003859322,0.002597944,0.00185294,0.001996193,0.1391568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002033175,"about_ca_system_score_gemma":0.003252167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02584729,"about_ca_topic_score_gemma":0.04105721,"domain_scores_codex":[0.9980425,0.0002426847,0.0004448306,0.0006807748,0.0003520434,0.0002371113],"domain_scores_gemma":[0.993076,0.002422218,0.0009627258,0.001373267,0.001850104,0.0003157102],"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":[0.0001932536,0.00002563044,0.002027839,0.001528,0.00003999188,0.00002555446,0.00003830122,0.0002437574,0.0001546361,0.001086088,0.9881027,0.006534199],"study_design_scores_gemma":[0.0001875031,0.00003087618,0.006000278,0.0009528445,0.0000484232,0.00007599521,0.0001363743,0.0003048936,0.0002921379,0.002068874,0.9898592,0.00004262502],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001288476,0.00009344429,0.00008569314,0.00005187173,0.00002699627,0.00001988789,0.9986084,0.0001590445,0.0008258164],"genre_scores_gemma":[0.0005763312,0.0001149252,0.0003289194,0.00007911401,0.0000103002,0.0001362644,0.9975878,0.00007860951,0.001087615],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.165989,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191906427334737,"score_gpt":0.4662227604251775,"score_spread":0.4443036961518301,"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."}}