{"id":"W2165922980","doi":"10.1145/1102351.1102482","title":"Learning from labeled and unlabeled data on a directed graph","year":2005,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":404,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cluster analysis; Spectral clustering; Directed graph; Graph; Undirected graph; Artificial intelligence; Theoretical computer science; Comparability graph; Clustering coefficient; Labeled data; Algorithm; Pattern recognition (psychology); Line graph; Voltage 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00494272,0.001115069,0.001798912,0.003677754,0.0008754431,0.002136834,0.003904695,0.002329801,0.00171025],"category_scores_gemma":[0.01368553,0.0007966088,0.001625694,0.003676264,0.002006063,0.004465685,0.002379321,0.002536259,0.0008983107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376213,"about_ca_system_score_gemma":0.001746871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003985701,"about_ca_topic_score_gemma":0.00655047,"domain_scores_codex":[0.9957538,0.002000404,0.0001920966,0.00109494,0.0007454085,0.0002133321],"domain_scores_gemma":[0.9905598,0.005658099,0.0007575313,0.001746465,0.000968091,0.0003100511],"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":[0.0001611898,0.0002620851,0.003492334,0.0005764486,0.0002444825,0.000372662,0.0002544618,0.4965028,0.004913913,0.1876717,0.007400502,0.2981475],"study_design_scores_gemma":[0.000017133,0.00003967225,0.0003070839,0.00002886716,0.00002345608,0.00006728223,0.00004258562,0.8437506,0.001127681,0.1515693,0.003004184,0.00002212765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002865923,0.0000994623,0.9960186,0.0001794843,0.00002065047,0.00004306568,0.0001596103,0.0002024971,0.0004107483],"genre_scores_gemma":[0.1442615,0.0006848094,0.8500258,0.0005237928,0.000169745,0.0004127169,0.001957342,0.0001403229,0.001823998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00494272,"threshold_uncertainty_score":0.02613991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02841037829395239,"score_gpt":0.2330074743013104,"score_spread":0.204597096007358,"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."}}