{"id":"W2425086070","doi":"10.17863/cam.4533","title":"The Mondrian Kernel","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Materials Research; Natural Sciences and Engineering Research Council of Canada; European Commission; Engineering and Physical Sciences Research Council; University of Oxford; Microsoft Research","keywords":"Mondrian; Kernel (algebra); Mathematics; Computer science; Discrete mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002925296,0.0002264857,0.0002451036,0.0002069697,0.0003455403,0.0002377635,0.00428089,0.0002059986,0.00005790843],"category_scores_gemma":[0.0001109846,0.0001381102,0.0002886363,0.001057988,0.0001973034,0.0002504076,0.004250502,0.0003521485,0.0005022978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000917631,"about_ca_system_score_gemma":0.00007895249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009945836,"about_ca_topic_score_gemma":0.00003424049,"domain_scores_codex":[0.9982529,0.0001358418,0.0001675379,0.0009467983,0.0001085257,0.0003883652],"domain_scores_gemma":[0.9972848,0.0003262705,0.0001999955,0.001911983,0.0001067452,0.0001701631],"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":[0.00000868869,0.00003989525,0.001248662,0.000005781231,0.0001443166,0.0001863844,0.00002382621,0.002204712,0.000004176321,0.9826322,0.003137839,0.01036358],"study_design_scores_gemma":[0.0003554498,0.00004906197,0.003761346,0.00003063738,0.0001009189,0.000004072178,0.00003834732,0.09380062,0.00004339561,0.8378234,0.06341086,0.0005819204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01490849,0.0002226893,0.9702605,0.001915407,0.0007592331,0.000130877,0.00003868832,0.0002378167,0.0115263],"genre_scores_gemma":[0.9823807,0.0005836192,0.0003208656,0.0001191804,0.00009517826,6.690484e-7,0.00000643141,0.000005908875,0.01648742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9699396,"threshold_uncertainty_score":0.795503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05966966449104814,"score_gpt":0.1794738153774394,"score_spread":0.1198041508863913,"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."}}