{"id":"W2812241481","doi":"10.3390/e20070519","title":"Projected Affinity Values for Nyström Spectral Clustering","year":2018,"lang":"en","type":"article","venue":"Entropy","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Eigenvalues and eigenvectors; Mathematics; Cluster analysis; Projection (relational algebra); Kernel (algebra); Kernel method; Gaussian function; Gaussian; Similarity (geometry); Quadratic equation; Point (geometry); Support vector machine; Applied mathematics; Combinatorics; Algorithm; Artificial intelligence; Computer science; Statistics","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":[0.002380518,0.001013461,0.001137336,0.001568626,0.001104438,0.002000147,0.001751389,0.001900745,0.003453911],"category_scores_gemma":[0.0125958,0.0005220855,0.000731646,0.001537591,0.001579069,0.002897266,0.002150276,0.001692403,0.001964935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259304,"about_ca_system_score_gemma":0.001417927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001836759,"about_ca_topic_score_gemma":0.001516746,"domain_scores_codex":[0.9976403,0.0007053551,0.0001477572,0.0003993149,0.0009841614,0.0001232135],"domain_scores_gemma":[0.9965963,0.001353849,0.0002923159,0.0005228557,0.001077273,0.0001574506],"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":[0.0003414617,0.0001924033,0.00209845,0.0003361281,0.0001284815,0.0001483435,0.0005018229,0.4343833,0.01241717,0.1504851,0.007318451,0.3916489],"study_design_scores_gemma":[0.0000112716,0.00002971163,0.0002890163,0.00002575367,0.000006098824,0.00006849971,0.00004130015,0.9580047,0.002358934,0.03662148,0.002518565,0.00002469593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006193524,0.000176123,0.9918948,0.00008414408,0.00004215387,0.00004952192,0.00004410594,0.0003037299,0.00121181],"genre_scores_gemma":[0.2752065,0.0003742183,0.7202665,0.0001824429,0.0001143948,0.0004125758,0.0004975614,0.0002794009,0.002666306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003453911,"threshold_uncertainty_score":0.01258957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02486172068981743,"score_gpt":0.278469608701322,"score_spread":0.2536078880115045,"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."}}