{"id":"W4237447107","doi":"10.1515/iupac.84.0582","title":"Gene Rearrangement","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Gene; Biology; Genetics; Computational 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002064101,0.0002552396,0.0002916275,0.00001629212,0.0001694429,0.00005377688,0.0003713419,0.0002271149,0.01753541],"category_scores_gemma":[0.0001060768,0.00007857945,0.0001283157,0.0001941986,0.00005125615,0.00003120258,0.0001537411,0.0001506488,0.00001026202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001143605,"about_ca_system_score_gemma":0.00007419138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002948393,"about_ca_topic_score_gemma":0.006294549,"domain_scores_codex":[0.9982988,0.00005437188,0.0002886901,0.0004006694,0.000644254,0.0003132441],"domain_scores_gemma":[0.9992577,0.00007747012,0.0001396249,0.0001577969,0.0002267062,0.0001406615],"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":[0.00001960673,0.0001234263,0.00000951618,0.0000072569,0.00003410816,0.00001167239,0.000001944887,1.629667e-7,0.003543489,0.00000326716,0.9679698,0.02827577],"study_design_scores_gemma":[0.0001842433,0.0002325202,0.0007174221,0.0000643477,0.00004852172,0.000007675712,0.000007218533,4.982958e-7,0.0001436542,0.0002355209,0.9980955,0.0002628952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002542246,0.0003814577,0.000001682033,0.00271978,0.0004491984,0.0002143886,0.9935862,0.00004667572,0.00005835656],"genre_scores_gemma":[0.00008369666,0.0008089005,0.0000223393,0.0003448153,0.002050823,0.00001761047,0.9961908,0.000001242838,0.0004798098],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03012571,"threshold_uncertainty_score":0.9833627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01872153126022877,"score_gpt":0.3389033593567979,"score_spread":0.3201818280965691,"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."}}