{"id":"W4404783470","doi":"10.18653/v1/2024.emnlp-main.535","title":"Fast Forwarding Low-Rank Training","year":2024,"lang":"en","type":"article","venue":"","topic":"Sports Performance and Training","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation; Open Philanthropy Project; National Science Foundation","keywords":"Training (meteorology); Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001598889,0.001983754,0.001457281,0.0006104742,0.0008015629,0.001380412,0.002126943,0.002443241,0.01291362],"category_scores_gemma":[0.01026512,0.0008092456,0.0007658468,0.0005319387,0.0008587493,0.002064402,0.001919255,0.002635428,0.006649256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008940971,"about_ca_system_score_gemma":0.00230507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008445934,"about_ca_topic_score_gemma":0.01856564,"domain_scores_codex":[0.9989852,0.0002327919,0.00005291562,0.0002370761,0.0003069318,0.0001851674],"domain_scores_gemma":[0.9971274,0.001403213,0.0001158633,0.0006227149,0.0006224739,0.0001082794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004555842,0.0002430604,0.001878859,0.0003112651,0.0001340665,0.0003984116,0.0001985474,0.5098928,0.01163887,0.01560757,0.05145258,0.4077883],"study_design_scores_gemma":[0.00003624699,0.00004492709,0.0001377834,0.00001495994,0.00001011073,0.00005233788,0.00001923678,0.988048,0.003452728,0.0053957,0.002776936,0.00001110308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02514849,0.0007871499,0.9482201,0.0008813765,0.0004968407,0.000185064,0.0006067608,0.01613089,0.007543323],"genre_scores_gemma":[0.4341305,0.0004820951,0.5366459,0.001101236,0.0003237097,0.0005530162,0.002714885,0.002623602,0.0214251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01291362,"threshold_uncertainty_score":0.04320037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03199218333011454,"score_gpt":0.2991447620347133,"score_spread":0.2671525787045987,"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."}}