{"id":"W4387385166","doi":"10.21272/jes.2023.10(2).e1","title":"Optimization of Cdx Transcription Factors Characteristics","year":2023,"lang":"en","type":"article","venue":"Journal of Engineering Sciences","topic":"Animal Genetics and Reproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Transcription factor; Repressor; Transcription (linguistics); TOPSIS; Computational biology; Biology; Gene; Computer science; Mathematics; Genetics; Operations research","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":[0.0008505216,0.000943982,0.000574833,0.001003951,0.0003366215,0.001470597,0.0003246187,0.0003369292,0.001639904],"category_scores_gemma":[0.001378621,0.0002950651,0.0007253264,0.0008699637,0.0002721022,0.0005143194,0.0004465583,0.0006506044,0.0005857077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007931741,"about_ca_system_score_gemma":0.0007892573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278385,"about_ca_topic_score_gemma":0.001655034,"domain_scores_codex":[0.9990172,0.0001179352,0.00006174554,0.0001863862,0.0005327651,0.00008397658],"domain_scores_gemma":[0.9995365,0.0001758173,0.00008154283,0.00003276458,0.0001461625,0.00002718331],"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":[0.000318782,0.0001119957,0.003975049,0.0004617192,0.00007376099,0.0001373113,0.0001287272,0.0961894,0.732381,0.003282468,0.0003410369,0.1625989],"study_design_scores_gemma":[0.00003765186,0.0007203688,0.006573172,0.00003789733,0.0001294635,0.0003236677,0.0002011698,0.3329197,0.6445043,0.002403155,0.0120767,0.00007275868],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2841645,0.001624717,0.7054104,0.0001239106,0.00005642125,0.0001659279,0.0003053157,0.0005940787,0.007554668],"genre_scores_gemma":[0.7196726,0.001007677,0.2735485,0.00003904326,0.00001546641,0.0001729926,0.0004858468,0.0001888759,0.004869002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001639904,"threshold_uncertainty_score":0.005754888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01575591357853504,"score_gpt":0.237104587944879,"score_spread":0.221348674366344,"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."}}