{"id":"W4312328230","doi":"10.1109/access.2022.3229008","title":"Topological Forest","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Topological and Geometric Data Analysis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Random forest; Metric (unit); Computer science; Topology (electrical circuits); Reduction (mathematics); Inference; Representation (politics); Decision tree; Mathematics; Artificial intelligence; Combinatorics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002110263,0.00006958374,0.0001207017,0.0001534171,0.0003028014,0.000185099,0.002903801,0.00002060337,0.001102098],"category_scores_gemma":[0.000045429,0.00005213416,0.00007334285,0.001690583,0.00003788229,0.0004271255,0.001492015,0.0001496579,0.00008277214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002616184,"about_ca_system_score_gemma":0.00001536536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001413661,"about_ca_topic_score_gemma":0.00001360613,"domain_scores_codex":[0.9989709,0.00007245079,0.0001305709,0.0003120469,0.0002954115,0.000218663],"domain_scores_gemma":[0.9993245,0.0001016899,0.00004892672,0.0004361658,0.00001939996,0.00006932681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002080434,0.0007220787,0.08739343,0.000007165408,0.00008962672,0.0005375323,0.0001420966,0.01276239,0.0001135435,0.6549487,0.09134407,0.1519185],"study_design_scores_gemma":[0.0007306329,0.0005067798,0.1344443,0.000001612685,0.00003437162,0.0001282409,0.00008063958,0.03517732,0.0006816043,0.3118247,0.5155832,0.0008065397],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3102592,0.0002036955,0.6700924,0.006155143,0.001334274,0.0001188649,0.00002648486,0.0003489771,0.01146099],"genre_scores_gemma":[0.9963908,0.000006916191,0.001073293,0.001716823,0.00006055716,0.00003505497,0.00000547171,0.000001833719,0.0007092324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6861317,"threshold_uncertainty_score":0.9998111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04576342813539561,"score_gpt":0.3044053996242905,"score_spread":0.2586419714888949,"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."}}