{"id":"W2403610646","doi":"10.1007/978-1-61779-361-5_12","title":"Algorithms for Systematic Identification of Small Subgraphs","year":2011,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research","keywords":"Biological network; Identification (biology); Computer science; Computational biology; Strengths and weaknesses; Graph; Task (project management); Data science; Artificial intelligence; Machine learning; Theoretical computer science; Biology; Engineering","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":[0.00305801,0.002618885,0.002266867,0.00566067,0.001497899,0.002034458,0.003818296,0.00191117,0.007019922],"category_scores_gemma":[0.02094395,0.001626578,0.002948284,0.003913361,0.001476936,0.004010859,0.003947247,0.00296939,0.002750748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001219022,"about_ca_system_score_gemma":0.002863716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002558653,"about_ca_topic_score_gemma":0.005566688,"domain_scores_codex":[0.9977761,0.0007630762,0.0001909447,0.0005300113,0.0005755465,0.0001643905],"domain_scores_gemma":[0.9833463,0.01162032,0.00066088,0.002347458,0.001676087,0.0003489529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006856811,0.0004263431,0.003284446,0.001260711,0.0003526374,0.0002477284,0.0004088224,0.1481091,0.01481437,0.05775091,0.01930673,0.7533526],"study_design_scores_gemma":[0.0002363993,0.00008461405,0.0006389541,0.00009009524,0.0001418553,0.0001432573,0.00008710571,0.8317508,0.004926676,0.1573597,0.004514381,0.00002629145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005744939,0.0002853671,0.9901066,0.0001566875,0.00002917029,0.0002163497,0.000393637,0.002443644,0.0006236146],"genre_scores_gemma":[0.04244369,0.0002505778,0.9529658,0.00009446671,0.00004220009,0.0005506893,0.002145445,0.0006006389,0.0009064654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007019922,"threshold_uncertainty_score":0.02348393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03863116556906254,"score_gpt":0.3562136608874269,"score_spread":0.3175824953183644,"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."}}