{"id":"W2003115311","doi":"10.1109/cvpr.2012.6248111","title":"Local Naive Bayes Nearest Neighbor for image classification","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Pooling; k-nearest neighbors algorithm; Computer science; Naive Bayes classifier; Contextual image classification; Merge (version control); Mathematics; Image (mathematics); Support vector machine","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":[0.0001853692,0.00009683907,0.00009456934,0.00004791,0.00009575982,0.00008659918,0.0003813152,0.00004866177,0.00002365564],"category_scores_gemma":[0.00008471066,0.00007881002,0.00005537874,0.000187691,0.00005828504,0.001783168,0.0001000863,0.00006263306,0.00007290691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003968842,"about_ca_system_score_gemma":0.00002321059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005860212,"about_ca_topic_score_gemma":7.80548e-7,"domain_scores_codex":[0.9992197,0.00001842161,0.0001430202,0.00020476,0.0001192381,0.0002949179],"domain_scores_gemma":[0.999247,0.0001230575,0.00005426303,0.0003527329,0.0001234427,0.00009952092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001337883,0.0001026632,0.0004144721,0.000019287,0.000007569153,0.00000105622,0.000196259,5.545435e-7,0.01620008,0.435482,0.01410952,0.5334532],"study_design_scores_gemma":[0.0004130294,0.000268388,0.008403749,0.00001891604,0.00001050347,0.00001841844,0.000155398,0.04773802,0.7123975,0.03175761,0.1983449,0.0004735282],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000125742,0.000163336,0.9931861,0.0006296099,0.0001271738,0.0002587911,0.000002862639,0.0004225808,0.0050838],"genre_scores_gemma":[0.4856599,0.00002422476,0.5133532,0.0003909954,0.00009409046,0.00004709814,0.000004254465,0.000008090432,0.0004181641],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6961974,"threshold_uncertainty_score":0.3213779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03453215885528536,"score_gpt":0.3230913751074366,"score_spread":0.2885592162521512,"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."}}