{"id":"W2082082456","doi":"10.1016/j.patcog.2013.11.006","title":"Near-duplicate document image matching: A graphical perspective","year":2013,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Science and Technology Commission of Shanghai Municipality","keywords":"Matching (statistics); Artificial intelligence; Computer science; Pattern recognition (psychology); Granularity; Segmentation; Object (grammar); Graph; Image segmentation; Tree (set theory); Perspective (graphical); Segmentation-based object categorization; Computer vision; Similarity (geometry); Image (mathematics); Mathematics; Scale-space segmentation; Theoretical computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001354162,0.0008838153,0.00113699,0.003722303,0.0007397175,0.003729347,0.002727834,0.002095707,0.01234074],"category_scores_gemma":[0.007545159,0.0006573785,0.0009209272,0.003594342,0.001446096,0.003968278,0.001854611,0.001015354,0.002493167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006205426,"about_ca_system_score_gemma":0.0005478953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00184259,"about_ca_topic_score_gemma":0.001321759,"domain_scores_codex":[0.9985996,0.0003643887,0.00009525094,0.0002978073,0.0005239162,0.0001190666],"domain_scores_gemma":[0.9974781,0.001101387,0.0002720377,0.0006442674,0.0004321642,0.0000721203],"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":[0.0007601798,0.0002334795,0.001395599,0.001084836,0.0001535779,0.001872992,0.000480657,0.05913603,0.05181672,0.3549771,0.01941503,0.5086738],"study_design_scores_gemma":[0.0001062742,0.0003393666,0.001298318,0.0001866161,0.0001509516,0.005260025,0.0003843473,0.5310981,0.05265295,0.3615663,0.04684076,0.0001159495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006519671,0.001315203,0.9820687,0.0008938686,0.0001757827,0.00007530024,0.0001769299,0.0009127594,0.007861795],"genre_scores_gemma":[0.353415,0.00383932,0.6239325,0.0005245664,0.0008203763,0.000125437,0.0005618552,0.0004336059,0.0163474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01234074,"threshold_uncertainty_score":0.04128385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01695951763831015,"score_gpt":0.2839185176384535,"score_spread":0.2669590000001434,"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."}}