{"id":"W3186747662","doi":"10.4049/jimmunol.1901228","title":"NR4A3 Mediates Thymic Negative Selection","year":2021,"lang":"en","type":"letter","venue":"The Journal of Immunology","topic":"Nuclear Receptors and Signaling","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôpital Maisonneuve-Rosemont","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Selection (genetic algorithm); Negative selection; Biology; Psychology; Computational biology; Computer science; Genetics; Artificial intelligence; Genome; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001812234,0.0004215307,0.0002519253,0.0002047976,0.0002257831,0.0003865418,0.0004434372,0.0002774746,0.002723013],"category_scores_gemma":[0.0001903469,0.0001395188,0.0003306514,0.0001034811,0.0003134437,0.0001991911,0.0004162087,0.0005001978,0.001300104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003018962,"about_ca_system_score_gemma":0.0002486406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007404221,"about_ca_topic_score_gemma":0.0008642965,"domain_scores_codex":[0.9997411,0.00004258817,0.00001905878,0.00004903323,0.00007206051,0.00007603728],"domain_scores_gemma":[0.9996865,0.0000292506,0.0001123407,0.00004018312,0.00004041706,0.0000913214],"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":[0.0001035508,0.000007027504,0.0002282136,0.00002040054,0.000002292261,0.00004346715,0.000005002797,0.00002106148,0.9988865,0.00008843526,0.00003823494,0.0005557228],"study_design_scores_gemma":[0.00003356405,0.0002187981,0.01213317,0.00001892374,0.00002828998,0.0007831393,0.00006513917,0.001308359,0.9805633,0.0002578736,0.004580224,0.000009292548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824645,0.004473534,0.00727394,0.0002505781,0.0001046468,0.00002049969,0.0007000705,0.0002883798,0.004423831],"genre_scores_gemma":[0.9938572,0.0007268174,0.001303332,0.00006108034,0.00002336475,0.00001286757,0.0004053997,0.00004173906,0.003568256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002723013,"threshold_uncertainty_score":0.009109378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02447941347251047,"score_gpt":0.2447533440907633,"score_spread":0.2202739306182528,"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."}}