{"id":"W2741312414","doi":"10.7939/r3c07x","title":"NOVEL MACHINE LEARNING ALGORITHMS","year":2013,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Artificial intelligence; Machine learning; Computer science; Decision tree; Naive Bayes classifier; Classifier (UML); Incremental decision tree; Focus (optics); Tree (set theory); Active learning (machine learning); Decision tree learning; Pattern recognition (psychology); Support vector machine; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000416635,0.0001094575,0.0001481485,0.0001188378,0.0001569642,0.00006465901,0.0008922794,0.00005448126,0.001021475],"category_scores_gemma":[0.00001874355,0.0001157318,0.00007942934,0.0002814777,0.00005628997,0.001611694,0.0005083161,0.0002363681,0.0002813094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000577152,"about_ca_system_score_gemma":0.00004030434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006204137,"about_ca_topic_score_gemma":0.00001598535,"domain_scores_codex":[0.9992628,0.00004916937,0.00009130958,0.0002597195,0.0001428088,0.0001942548],"domain_scores_gemma":[0.9993367,0.0001531359,0.00009138921,0.0002812004,0.0000222449,0.0001153099],"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":[0.0000514231,0.001223107,0.1219965,0.0002183209,0.000443871,0.0001231607,0.03673018,0.00578908,0.004342129,0.1557732,0.04989362,0.6234154],"study_design_scores_gemma":[0.0008246752,0.0001562566,0.01392516,0.00003494829,0.000008961467,0.00002427228,0.0002371573,0.8465765,0.0004854295,0.0006174478,0.1367727,0.0003364623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1024522,0.0002503039,0.7074023,0.0164044,0.0004549741,0.000346548,0.000003520565,0.0007946617,0.171891],"genre_scores_gemma":[0.3305719,0.00006748764,0.514949,0.0004574163,0.0001074336,3.417835e-7,0.00004748135,0.00003028962,0.1537687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8407875,"threshold_uncertainty_score":0.9998917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006413709727114704,"score_gpt":0.17068589177247,"score_spread":0.1642721820453553,"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."}}