{"id":"W2294194070","doi":"10.1142/s0219720016410055","title":"Sequential construction of a model for modular gene expression control, applied to spatial patterning of the<i>Drosophila</i>gene<i>hunchback</i>","year":2016,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; British Columbia Institute of Technology","funders":"National Institute of General Medical Sciences; National Institutes of Health; Russian Foundation for Basic Research","keywords":"Gene regulatory network; Gene; Biology; Computational biology; Cis-regulatory module; Regulation of gene expression; Genetics; Gene expression; Regulator gene; Regulatory sequence; Transcription factor; Translation (biology); Regulator; Gap gene; Transcription (linguistics); Messenger RNA; Promoter","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":[0.0006538716,0.000606516,0.0005991868,0.0003791551,0.0005837256,0.0005805395,0.0008109713,0.001128606,0.002759377],"category_scores_gemma":[0.001515143,0.0004484738,0.0007922585,0.0004869439,0.001040065,0.0004557579,0.0007606387,0.0007929036,0.000256429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001357839,"about_ca_system_score_gemma":0.001504792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01216045,"about_ca_topic_score_gemma":0.008412197,"domain_scores_codex":[0.9998257,0.00007770714,0.000006789612,0.00003856097,0.00003315384,0.00001814601],"domain_scores_gemma":[0.9994186,0.0003977116,0.00006196948,0.00002070218,0.00006021183,0.00004088967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001094154,0.00000561465,0.0001102092,0.000009519861,0.000003435887,0.00002324276,0.000008818743,0.9928774,0.0004966899,0.005650946,0.00007100539,0.0007322826],"study_design_scores_gemma":[0.000002909833,0.000003399137,0.00001670098,7.257805e-7,0.000001144594,0.000001943987,0.000001246394,0.9988436,0.00007239576,0.0009689421,0.00008626965,8.421305e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07696465,0.0001612514,0.9141309,0.000417733,0.0000509875,0.00009680665,0.000274066,0.0002376469,0.007665983],"genre_scores_gemma":[0.8096321,0.0003540795,0.1792002,0.0001079213,0.0000328198,0.0007630559,0.0003838427,0.0001662905,0.009359585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01216045,"threshold_uncertainty_score":0.02417934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008403906487245838,"score_gpt":0.2224337522941265,"score_spread":0.2140298458068807,"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."}}