{"id":"W4234853714","doi":"10.1515/iupac.88.1077","title":"Mosaicism","year":2017,"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; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001410499,0.001008857,0.001398797,0.0004774778,0.0005055547,0.0004061436,0.002351186,0.0009286441,0.007457298],"category_scores_gemma":[0.002358525,0.0009417297,0.000399167,0.0001902589,0.00049768,0.0002480354,0.0006802386,0.001592792,0.0004790569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001163156,"about_ca_system_score_gemma":0.00213883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006780905,"about_ca_topic_score_gemma":0.006582738,"domain_scores_codex":[0.9940747,0.0001590995,0.0007338045,0.001081133,0.002974348,0.0009769419],"domain_scores_gemma":[0.9927387,0.00008789269,0.001096498,0.00464814,0.001002991,0.0004258311],"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":[0.0002421011,0.0003552953,0.00000431323,0.0001515428,0.0002362784,0.0004911862,0.0000082034,0.000003138784,0.00001107194,0.00000468535,0.9975823,0.0009098625],"study_design_scores_gemma":[0.001409188,0.0001809115,0.0000462375,0.0004844208,0.0004048315,0.00005518474,0.000009739336,0.00001012059,0.00001259364,0.0001910061,0.9961933,0.001002491],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003823543,0.001231488,0.00001189788,0.0002521208,0.001839978,0.0005267853,0.9955119,0.000300297,0.0002873158],"genre_scores_gemma":[0.000004957682,0.0002984652,0.00008747572,0.0002110053,0.002334705,0.00002756158,0.99487,0.0002793762,0.00188646],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006978241,"threshold_uncertainty_score":0.9993033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02409601182618215,"score_gpt":0.4630822864702477,"score_spread":0.4389862746440655,"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."}}