{"id":"W2952274870","doi":"10.48550/arxiv.1310.8089","title":"Reducing complexes in multidimensional persistent homology theory","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Bishop's University","funders":"","keywords":"Discrete Morse theory; Correctness; Morse code; Mathematics; Persistent homology; Polygon mesh; Matching (statistics); Simplicial complex; Reduction (mathematics); Homology (biology); Morse theory; Algorithm; Computer science; Combinatorics; Pure mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004256235,0.0002695422,0.0004553979,0.0007757053,0.0001223663,0.00006430353,0.001764658,0.0002770323,0.0003294224],"category_scores_gemma":[0.0001079066,0.0002553371,0.0003458367,0.001199846,0.0002220836,0.0002611692,0.003647266,0.0005894644,0.0002567835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000172416,"about_ca_system_score_gemma":0.00008444628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0012001,"about_ca_topic_score_gemma":0.00003298757,"domain_scores_codex":[0.9976374,0.0003696913,0.0002470113,0.001237082,0.00009801701,0.000410819],"domain_scores_gemma":[0.9981121,0.0003586265,0.0001915356,0.001073265,0.0001078861,0.000156625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001926372,0.0002546743,0.002516921,0.00002495587,0.0001795227,0.0004537113,0.000203892,0.235125,0.00004221241,0.7587011,0.0006413756,0.00183732],"study_design_scores_gemma":[0.0006928854,0.000121446,0.01910287,0.00007709092,0.0001292251,0.00002141061,0.0003017858,0.7529397,0.00003776492,0.2249494,0.0008400965,0.0007863166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7518146,0.0003063927,0.2456113,0.0002796081,0.0003635051,0.0001893864,0.00002343749,0.0001243761,0.001287406],"genre_scores_gemma":[0.9935258,0.0001175007,0.004202158,0.0001463116,0.00003261944,0.000001303671,0.00003990809,0.000006342974,0.001928039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5337517,"threshold_uncertainty_score":0.9999899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07405416942672052,"score_gpt":0.1947448019288083,"score_spread":0.1206906325020878,"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."}}