{"id":"W3134176997","doi":"10.21203/rs.3.rs-180857/v1","title":"Knowledgebase Approximation Using Association Rules Aggregation","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Association (psychology); Association rule learning; Computer science; Computational biology; Data mining; Biology; Epistemology; Philosophy","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002754954,0.0001842897,0.0002354548,0.0003953575,0.0004740169,0.001785014,0.001120306,0.0003303535,0.00002852758],"category_scores_gemma":[0.0009994857,0.0002007587,0.0001147393,0.0008923921,0.00003765305,0.0006241485,0.002380084,0.0010387,0.000127269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001107377,"about_ca_system_score_gemma":0.0008870675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002799121,"about_ca_topic_score_gemma":0.00003092855,"domain_scores_codex":[0.9964019,0.0005884846,0.0003484278,0.0008443525,0.001328962,0.0004878837],"domain_scores_gemma":[0.9962212,0.000377861,0.0002514237,0.001292581,0.001720851,0.000136086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007247382,0.001093267,0.002779281,0.002155585,0.0002236472,0.00005099574,0.006801131,0.003097819,0.002463376,0.048666,0.01106568,0.921596],"study_design_scores_gemma":[0.0001564505,0.00002350609,0.001730931,0.0007824631,0.00001115693,0.000003567668,0.0002319536,0.985059,0.001954029,0.006779361,0.002987607,0.00027995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08661741,0.00104786,0.9075681,0.001277198,0.0005214266,0.0009241373,0.0001551359,0.0002880714,0.001600657],"genre_scores_gemma":[0.1908845,0.0005011369,0.8023647,0.00004586599,0.001110481,0.0007420264,0.00291981,0.00006539409,0.001366047],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9819612,"threshold_uncertainty_score":0.9992512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1009140366716022,"score_gpt":0.40475197032005,"score_spread":0.3038379336484478,"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."}}