{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002307849,0.0008144978,0.0009924402,0.001936225,0.0008953626,0.002933275,0.00194591,0.001430264,0.005652016],"category_scores_gemma":[0.01685563,0.0004811413,0.001112089,0.001478379,0.00181459,0.00508078,0.002992416,0.002604476,0.002649389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009055402,"about_ca_system_score_gemma":0.001067518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001756771,"about_ca_topic_score_gemma":0.001399836,"domain_scores_codex":[0.9983852,0.0004510357,0.00008632066,0.0003949436,0.0004664164,0.0002161076],"domain_scores_gemma":[0.9962203,0.001322171,0.0004016938,0.001131729,0.0006463844,0.0002778064],"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":[0.0000617847,0.00003412482,0.001867211,0.0001091566,0.00003769389,0.0001397328,0.0001621427,0.02723745,0.001826019,0.8860742,0.007630355,0.0748201],"study_design_scores_gemma":[0.0000109969,0.00003630902,0.001065202,0.00006828717,0.00001931659,0.0004310128,0.00005484768,0.3537257,0.001689188,0.6051092,0.03774202,0.00004793183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009722613,0.0009227567,0.9821314,0.0004364034,0.0001635655,0.00003150278,0.0002390229,0.0003946914,0.005958086],"genre_scores_gemma":[0.4116867,0.002711515,0.5659302,0.0008138583,0.0007565204,0.0002298233,0.001113241,0.000820988,0.01593718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005652016,"threshold_uncertainty_score":0.01890785,"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."}}