{"id":"W4244769347","doi":"10.7287/peerj.preprints.26593v1","title":"MIPhy: Identify and quantify rapidly evolving members of large gene families","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Phylogenetic tree; Gene duplication; Biology; Gene; Gene family; Phylogenetics; Caenorhabditis; Evolutionary biology; Lineage (genetic); Genetics; Clade; Caenorhabditis elegans; Phenotype; Organism; Computational biology; Gene expression","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":[0.0003325029,0.0002321316,0.0002841477,0.00008892394,0.00004269251,0.00002827415,0.0001678643,0.000371058,0.0000604227],"category_scores_gemma":[0.0000967808,0.0002155655,0.0001163117,0.00005470704,0.00009643204,0.000002438739,0.0005075591,0.0001486116,0.000003872807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006063418,"about_ca_system_score_gemma":0.00004350496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001725969,"about_ca_topic_score_gemma":0.00005148868,"domain_scores_codex":[0.9988251,0.00003631786,0.0002898604,0.0005381947,0.0001027191,0.000207752],"domain_scores_gemma":[0.999142,0.000002417595,0.0001359857,0.0004997356,0.0001678681,0.0000520234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000185347,0.00002878308,0.0004685149,0.0002484223,0.0001275073,3.866039e-7,0.00005675792,0.00005548817,0.9948265,0.0000265418,0.003786553,0.0003560436],"study_design_scores_gemma":[0.0002375016,0.00006346752,0.004112199,0.00006201903,0.00006486721,0.00001055656,0.00006660637,0.0001381847,0.9756787,0.00003800093,0.0192427,0.0002852063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894423,0.005138294,0.003462261,0.00004932483,0.001135517,0.0001784524,0.00007613669,0.0000269461,0.0004907846],"genre_scores_gemma":[0.9886028,0.003025042,0.006325856,0.00003953397,0.0007859223,0.000007809035,0.0002410748,0.00002920208,0.000942736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01914778,"threshold_uncertainty_score":0.8790504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009660969295565,"score_gpt":0.2689234552241906,"score_spread":0.258826845531235,"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."}}