{"id":"W4252714558","doi":"10.1007/978-1-4614-6170-8_100619","title":"Subgraph Evolution","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science","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":[0.0001730265,0.0006027966,0.0004381676,0.0006935853,0.0004644259,0.0007186483,0.001027455,0.0005666774,0.03598319],"category_scores_gemma":[0.0006521434,0.0002711233,0.0005548418,0.001027815,0.0005913343,0.001073646,0.001144272,0.001226358,0.008406075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007670036,"about_ca_system_score_gemma":0.0005118989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001639029,"about_ca_topic_score_gemma":0.003695182,"domain_scores_codex":[0.9998283,0.00003118587,0.000004491987,0.00005039078,0.00006946596,0.0000160081],"domain_scores_gemma":[0.9998612,0.00003915856,0.000005701469,0.00005058889,0.00002983325,0.00001345951],"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":[0.00002643609,0.00005364483,0.0002184397,0.000273045,0.00003544574,0.00007422788,0.0001056967,0.03866804,0.006629966,0.3640977,0.09535637,0.4944611],"study_design_scores_gemma":[0.00001648802,0.00003580012,0.0003832788,0.0001131805,0.0000351731,0.0002900487,0.00006499513,0.1072721,0.007185224,0.4192926,0.4652845,0.00002658509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00762433,0.003202575,0.5385211,0.001267864,0.0007099077,0.0001518043,0.0008130172,0.002005271,0.4457042],"genre_scores_gemma":[0.1587895,0.006277158,0.3830536,0.001125334,0.0003643485,0.0003427581,0.00443519,0.002859869,0.4427523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03598319,"threshold_uncertainty_score":0.1203757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008996404569286206,"score_gpt":0.1909609863998464,"score_spread":0.1819645818305602,"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."}}