{"id":"W4400682287","doi":"10.1145/3672198.3673793","title":"Proof-of-Concept of a Flexible and High-Fidelity Approach to Distributed DNN Training Emulation","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Emulation; Computer science; Fidelity; Proof of concept; Training (meteorology); High fidelity; Computer architecture; Distributed computing; Operating system; Engineering; Psychology; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.000100224,0.000083976,0.0001452544,0.00006984947,0.00001227391,0.00001724031,0.00006768914,0.00004601273,0.000007562164],"category_scores_gemma":[0.00003605996,0.00007792667,0.0000145285,0.0002701583,0.00002883552,0.0002224459,0.00003449058,0.00006861744,2.924545e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002754701,"about_ca_system_score_gemma":0.00001404064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000134706,"about_ca_topic_score_gemma":5.538752e-7,"domain_scores_codex":[0.9994482,0.000005810721,0.000207618,0.0001494422,0.00008316754,0.0001057531],"domain_scores_gemma":[0.9997424,0.00003398472,0.00001585879,0.0001415685,0.00003156714,0.00003457902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002196308,0.00006458513,0.00005562539,0.001921473,0.00009521397,0.000001897882,0.004980346,0.08698273,0.0212129,0.04774036,0.002520451,0.8344024],"study_design_scores_gemma":[0.0001077168,0.00005649706,0.0002144121,0.0002455541,0.00001750678,0.000003894881,0.0002799297,0.3131261,0.6745202,0.01027709,0.0009429899,0.0002081358],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01911032,0.000592593,0.9784015,0.00001607301,0.00003761069,0.0001620965,0.0001110938,0.0007430174,0.000825702],"genre_scores_gemma":[0.7925044,0.000001188654,0.2073396,0.000002982046,0.00001391531,0.00001972026,0.00008763061,0.00001372092,0.00001680856],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8341943,"threshold_uncertainty_score":0.3177757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03408917210478044,"score_gpt":0.28233302196355,"score_spread":0.2482438498587696,"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."}}