{"id":"W4417113221","doi":"10.3390/app152412918","title":"Bio-Inspired Generative Network with Knowledge Integration","year":2025,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Interpretability; Biological data; Data integration; Gene regulatory network; Cluster analysis; Robustness (evolution); Generative model; Synthetic data; Biological network; Discriminator","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":[0.0007072881,0.0007099231,0.0004479273,0.0004492041,0.0001940671,0.0005809311,0.001076117,0.0007508,0.001778825],"category_scores_gemma":[0.002323228,0.0003650608,0.0006567208,0.0004235109,0.0008916474,0.0008336366,0.001353439,0.001263017,0.0003704159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008054567,"about_ca_system_score_gemma":0.0004511231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00181726,"about_ca_topic_score_gemma":0.00245246,"domain_scores_codex":[0.9997078,0.00009392144,0.000009039924,0.00009395271,0.00007226186,0.00002304739],"domain_scores_gemma":[0.9990355,0.0006660397,0.00007833251,0.0001096928,0.00007353524,0.00003695906],"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":[0.00001831291,0.00001335669,0.0003325298,0.00002542197,0.00001636308,0.00004638261,0.00002297468,0.9744738,0.00233931,0.01168281,0.0004551478,0.0105736],"study_design_scores_gemma":[0.000001517764,0.000004372446,0.00003099824,0.000001863527,0.000001682072,0.00001127168,0.000001780175,0.9931809,0.000515079,0.005962816,0.0002858052,0.000002044417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01986544,0.0001499347,0.9768535,0.0002456751,0.0000288992,0.00002661349,0.0001861423,0.0004548935,0.002188972],"genre_scores_gemma":[0.7798217,0.0003318701,0.2116959,0.0004282185,0.0000462506,0.0002711008,0.001094991,0.0002855171,0.006024362],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00181726,"threshold_uncertainty_score":0.005950689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009215897681991533,"score_gpt":0.2451461050891147,"score_spread":0.2359302074071232,"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."}}