{"id":"W2563968870","doi":"10.1109/cibcb.2016.7758126","title":"Evolving graph compression using similarity measures for bioinformatics applications","year":2016,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Crossover; Computer science; Graph; Similarity (geometry); Theoretical computer science; Modular decomposition; Data compression; Data mining; Algorithm; Artificial intelligence; Pathwidth; Line graph","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":[],"consensus_categories":[],"category_scores_codex":[0.0001474295,0.0001004082,0.0001033912,0.0000437839,0.0001475284,0.00001637002,0.0001382522,0.00009788721,0.00001677559],"category_scores_gemma":[0.00002845486,0.00006732126,0.0001286126,0.00008519334,0.00004904091,0.00000482588,0.00006772815,0.0000176058,0.00000285452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001320815,"about_ca_system_score_gemma":0.00003395017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002914148,"about_ca_topic_score_gemma":0.00001686033,"domain_scores_codex":[0.999352,0.00001880207,0.0001864328,0.0001739346,0.00009542891,0.0001734317],"domain_scores_gemma":[0.9993412,0.00001428765,0.00007858498,0.0003456055,0.0001560427,0.00006424356],"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":[0.00001730341,0.00003482718,0.00411831,0.00002447434,0.0001161726,4.487484e-8,0.000009907017,0.0005961533,0.966199,0.0002131396,0.004889827,0.02378081],"study_design_scores_gemma":[0.001524122,0.0001356812,0.002452913,0.00006821214,0.0002863219,0.00001077503,0.000136044,0.03935889,0.7934769,0.003246409,0.1585151,0.0007886193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04547004,0.0003379462,0.9532717,0.00009824811,0.000030152,0.0002639272,0.00001569359,0.0000193028,0.0004929886],"genre_scores_gemma":[0.947997,0.00005768354,0.05133884,0.00009240221,0.0001525407,0.00004496821,0.00003330845,0.00001432964,0.0002689259],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.902527,"threshold_uncertainty_score":0.2745281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.022232868545274,"score_gpt":0.2699936205688718,"score_spread":0.2477607520235978,"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."}}