{"id":"W4416875187","doi":"10.1109/qce65121.2025.00247","title":"Identifying Protein Co-Regulatory Network Logic by Solving B-Sat Problems Through Gate-Based Quantum Computing","year":2025,"lang":"","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Context (archaeology); Heuristic; Constraint satisfaction problem; Boolean satisfiability problem; Domain (mathematical analysis); Constraint (computer-aided design); Quantum computer; Computational complexity theory","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001657603,0.001220528,0.001254963,0.0001798563,0.001387813,0.0004902189,0.001134561,0.001166315,0.0002486822],"category_scores_gemma":[0.00008913472,0.001289686,0.0009970302,0.001363725,0.0006349271,0.00002839351,0.0007569159,0.0006479836,0.00007628923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002675031,"about_ca_system_score_gemma":0.000841315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001090147,"about_ca_topic_score_gemma":0.00009958602,"domain_scores_codex":[0.992117,0.0008518259,0.001865131,0.002351486,0.0006910748,0.002123444],"domain_scores_gemma":[0.9964121,0.00008932874,0.0009081595,0.001877271,0.000415834,0.0002973065],"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":[0.0002088031,0.0006177086,0.01198388,0.001636714,0.002649895,0.00001986151,0.0001241137,0.3487131,0.5545622,0.003508648,0.07234725,0.003627808],"study_design_scores_gemma":[0.005056299,0.0007210465,0.001177382,0.003391178,0.001701533,0.00001559845,0.0006719807,0.4225527,0.4520235,0.007205463,0.1012295,0.004253802],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4577608,0.0626822,0.4688649,0.001092946,0.001210212,0.002669662,0.0000338894,0.0002167268,0.00546867],"genre_scores_gemma":[0.985639,0.0003070764,0.005685798,0.001606228,0.0007761997,0.00008084343,0.0007359391,0.0001382633,0.005030596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5278783,"threshold_uncertainty_score":0.9999123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597475607664842,"score_gpt":0.2716584514084316,"score_spread":0.2556836953317831,"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."}}