{"id":"W4254820525","doi":"10.32920/14638272.v1","title":"Gene Network Landscape of the Ciliate Tetrahymena thermophila","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Protist diversity and phylogeny","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Toronto Metropolitan University","funders":"Canadian Institutes of Health Research; National Institutes of Health; National Natural Science Foundation of China; University of Rochester","keywords":"Tetrahymena; Gene; Ciliate; Biology; Context (archaeology); DNA microarray; Genetics; Computational biology; Gene regulatory network; Microarray; Gene expression","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":[0.00008511008,0.0001033159,0.0001892181,0.0009039513,0.0003602221,0.0002859702,0.0001338756,0.0002052488,0.001139333],"category_scores_gemma":[0.0004258643,0.00008224125,0.0002374385,0.0009929347,0.0002114599,0.0002374731,0.0001897646,0.0001057661,0.0001396696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005368121,"about_ca_system_score_gemma":0.0002696151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004522024,"about_ca_topic_score_gemma":0.004443464,"domain_scores_codex":[0.99993,0.00001004298,0.000003111154,0.00003194681,0.00001337699,0.0000114917],"domain_scores_gemma":[0.9997579,0.00007315877,0.00006444956,0.00001400428,0.00005917998,0.00003117154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006812379,0.00005977393,0.2316829,0.0006334215,0.0002117323,0.0004922061,0.000888026,0.0456231,0.6769568,0.003451593,0.002186148,0.03713297],"study_design_scores_gemma":[0.00002418018,0.0002016204,0.8168467,0.0000332829,0.0001578286,0.0005636085,0.0006420515,0.147085,0.02565255,0.00395501,0.004800322,0.00003781917],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945191,0.0002897047,0.002849699,0.00006258382,0.000003211151,0.000007644714,0.001550082,0.00008023079,0.0006378505],"genre_scores_gemma":[0.9943973,0.0001294826,0.003371495,0.00002461205,0.000002970202,0.00002078379,0.001664649,0.00001686818,0.0003718412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004522024,"threshold_uncertainty_score":0.00899142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027073561298376,"score_gpt":0.2067067176134324,"score_spread":0.1964359820004487,"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."}}