{"id":"W2552791835","doi":"10.5555/3192424.3192606","title":"Spectral graph-based semi-supervised learning for imbalanced classes","year":2016,"lang":"en","type":"article","venue":"Advances in Social Networks Analysis and Mining","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Embedding; Graph; Computer science; Semi-supervised learning; Graph embedding; Theoretical computer science; Pattern recognition (psychology); Artificial intelligence; Mathematics; Algorithm; Combinatorics","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":[0.0002450134,0.0001271669,0.0002878276,0.0002483256,0.0002685722,0.00009592086,0.0003031455,0.00008626781,0.000006077456],"category_scores_gemma":[0.00006091671,0.00009564603,0.0001452548,0.001215126,0.0001087407,0.0005198217,0.00005874509,0.00008028182,3.240968e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003047423,"about_ca_system_score_gemma":0.00001562985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002977771,"about_ca_topic_score_gemma":0.00007655707,"domain_scores_codex":[0.998899,0.00004550952,0.0002501607,0.0003807726,0.0001151247,0.0003094766],"domain_scores_gemma":[0.9992455,0.0003709019,0.000158446,0.0001495883,0.00004367802,0.00003188053],"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":[0.0000220608,0.00002985633,0.2313069,0.000009356226,0.000105499,0.000001673445,0.0002530209,0.01837491,0.0003645512,0.02877938,0.00009056059,0.7206622],"study_design_scores_gemma":[0.001857016,0.0001948145,0.05499355,0.00008489474,0.0002032585,4.498487e-7,0.001116904,0.9097817,0.0007865066,0.01690367,0.01336682,0.0007104159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04502913,0.001269266,0.9522613,0.0008855609,0.00007372158,0.00008508557,8.807104e-7,0.0001697042,0.0002253484],"genre_scores_gemma":[0.9789628,0.0009847336,0.01973901,0.00007348719,0.00008647701,0.00005185066,0.000004899662,0.000006096653,0.00009064042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9339337,"threshold_uncertainty_score":0.3900332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01270324698367037,"score_gpt":0.2806359572578104,"score_spread":0.2679327102741401,"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."}}