{"id":"W1967648182","doi":"10.1007/s00373-007-0714-3","title":"Efficient Many-To-Many Point Matching in One Dimension","year":2007,"lang":"en","type":"article","venue":"Graphs and Combinatorics","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Interdisciplinary Research in Music Media and Technology; Queen's University; McGill University","funders":"","keywords":"Combinatorics; Mathematics; Cardinality (data modeling); Matching (statistics); Dimension (graph theory); Point (geometry); Context (archaeology); 3-dimensional matching; Line (geometry); Discrete mathematics; Bipartite graph; Computer science; Graph; Statistics; Geometry","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":[0.0009020658,0.001157302,0.002683084,0.001305245,0.001726984,0.003842781,0.003649377,0.002476383,0.01107726],"category_scores_gemma":[0.005170639,0.0007383315,0.001123605,0.003884692,0.001256359,0.008936671,0.004392412,0.001747224,0.002964672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771857,"about_ca_system_score_gemma":0.001873767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002329535,"about_ca_topic_score_gemma":0.003220005,"domain_scores_codex":[0.9979959,0.0004498321,0.0001382918,0.0005025999,0.0004862323,0.0004272834],"domain_scores_gemma":[0.9970635,0.0011484,0.0002518312,0.001092796,0.0002126486,0.0002307933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00224707,0.001067002,0.003232022,0.001203556,0.000336731,0.0003614708,0.0006498168,0.1724087,0.02567092,0.3985629,0.03370548,0.3605544],"study_design_scores_gemma":[0.0003090526,0.0001884556,0.0006724583,0.00004592873,0.0001577418,0.0002497142,0.0003002383,0.3944966,0.009987272,0.5861783,0.007358825,0.00005535076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3407536,0.001420553,0.6011994,0.002803745,0.0003277693,0.0004613357,0.001778106,0.005254494,0.04600111],"genre_scores_gemma":[0.6848574,0.0007422398,0.2938136,0.0005078377,0.0001081286,0.0002525856,0.001532741,0.0004785615,0.017707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01107726,"threshold_uncertainty_score":0.0370571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663249054649343,"score_gpt":0.2347373155353467,"score_spread":0.2181048249888533,"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."}}