{"id":"W2141629057","doi":"10.1093/bioinformatics/btl030","title":"Efficient estimation of graphlet frequency distributions in protein–protein interaction networks","year":2006,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Scalability; Heuristic; Computer science; Biological network; Software; Algorithm; Theoretical computer science; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001608615,0.0005503147,0.0007979289,0.002244009,0.0004027052,0.000925332,0.001263722,0.001080856,0.00123061],"category_scores_gemma":[0.01414431,0.0005523796,0.0005122674,0.001565604,0.0006459745,0.001529157,0.00082329,0.0009700888,0.000753876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033536,"about_ca_system_score_gemma":0.0006919176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002905722,"about_ca_topic_score_gemma":0.003143906,"domain_scores_codex":[0.9994144,0.0002130512,0.00002742634,0.0001032968,0.0001929862,0.00004886822],"domain_scores_gemma":[0.9922732,0.006092172,0.0006256597,0.0004426094,0.0004069142,0.0001594561],"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":[0.0002851895,0.00010735,0.009635455,0.0002292996,0.00007392588,0.0001826477,0.0001965882,0.8393086,0.01028676,0.0106363,0.002922788,0.1261351],"study_design_scores_gemma":[0.000007702194,0.000008343653,0.0007788947,0.000003811394,0.000003004048,0.00003996282,0.00001117655,0.992368,0.001149335,0.005423998,0.0002014147,0.000004322278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09489736,0.0002918128,0.9023466,0.0002289769,0.00001500912,0.00005608323,0.0003434697,0.001149871,0.0006708202],"genre_scores_gemma":[0.5127156,0.0003589434,0.4834521,0.00007908195,0.00005160026,0.0001714151,0.002125067,0.0001933153,0.0008528464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002905722,"threshold_uncertainty_score":0.008507252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005303035860545529,"score_gpt":0.2172868372395253,"score_spread":0.2119838013789798,"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."}}