{"id":"W1876649195","doi":"10.1007/978-3-030-63416-2_775","title":"Many-to-Many Graph Matching","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Matching (statistics); Computer science; Graph; Theoretical computer science; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002580532,0.0003582475,0.0003643766,0.0003122506,0.0001566122,0.00029593,0.001356083,0.0002018547,0.0007752508],"category_scores_gemma":[0.000004627779,0.0003299842,0.0003126948,0.0001161146,0.00003896331,0.0002140293,0.0007598533,0.0004028103,0.0009391762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001974643,"about_ca_system_score_gemma":0.00004817612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007330344,"about_ca_topic_score_gemma":0.000004973469,"domain_scores_codex":[0.9982269,0.00002352639,0.0002905485,0.0007654873,0.0003658335,0.0003276751],"domain_scores_gemma":[0.9984829,0.00007212762,0.00008965726,0.001068289,0.00008132669,0.0002057418],"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":[8.648985e-7,0.000007444565,2.732112e-7,0.00001313774,0.00004072649,0.0001726865,0.000144233,0.00001524426,0.00002811016,0.9800223,0.001166736,0.01838822],"study_design_scores_gemma":[0.00007979222,0.00003562749,0.00000809072,0.0001457987,0.00001246381,0.00005382354,0.00001223406,0.0001875486,0.0001337916,0.9080179,0.09081527,0.0004976267],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.000009672976,0.0001612973,0.5104888,0.0003385303,0.0006533226,0.00008958532,0.000003902053,0.0001925742,0.4880623],"genre_scores_gemma":[0.0006093574,0.00005413593,0.07127753,0.002443489,0.0002031084,0.000007623427,0.000009354252,0.00004120676,0.9253542],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4392113,"threshold_uncertainty_score":0.9999152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0140425456782824,"score_gpt":0.2193379846512718,"score_spread":0.2052954389729894,"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."}}