{"id":"W4394810076","doi":"10.1089/cmb.2023.0400","title":"Orthology and Paralogy Relationships at Transcript Level","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Gene; Biology; Ensembl; Genetics; Homology (biology); Orthologous Gene; Transcriptome; Homologous chromosome; Gene family; Computational biology; Genome; Gene expression; Genomics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003513023,0.00008602344,0.0001409326,0.00008644094,0.00006819526,0.0000149488,0.00007824127,0.0001680973,0.00002113633],"category_scores_gemma":[0.00002649492,0.00006992531,0.00007772381,0.00005042682,0.0001259216,0.000005528206,0.0000389022,0.0001746759,0.000009603004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001307035,"about_ca_system_score_gemma":0.00009051389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.131925e-7,"about_ca_topic_score_gemma":0.000009722104,"domain_scores_codex":[0.9992787,0.00008362729,0.0003593011,0.0001095149,0.00004779673,0.0001210884],"domain_scores_gemma":[0.9996,0.00009517749,0.0001025631,0.00005419153,0.00008782076,0.00006025595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001690065,0.0002569176,0.07087522,0.0003585914,0.002622462,0.0002200658,0.002765084,0.06040246,0.2306866,0.3589159,0.1149198,0.1562868],"study_design_scores_gemma":[0.002647604,0.002846471,0.1036365,0.00009149823,0.0001961993,0.01189709,0.0001915569,0.01753921,0.001407908,0.4037261,0.4551017,0.0007181788],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8112763,0.008053086,0.1776117,0.001749077,0.0006946754,0.00006104459,0.00003969475,0.000005739646,0.0005086829],"genre_scores_gemma":[0.9927194,0.0002003376,0.006160231,0.0003282761,0.0002916214,0.00000118146,0.00009474029,0.000007874332,0.0001963973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3401819,"threshold_uncertainty_score":0.2851471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03314015103441619,"score_gpt":0.2735098467436939,"score_spread":0.2403696957092777,"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."}}