{"id":"W4404996195","doi":"10.1103/gxrh-2xsv","title":"Surveying the Space of Descriptions of a Composite System with Machine Learning","year":2025,"lang":"en","type":"preprint","venue":"Physical Review Letters","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Army Research Office","keywords":"Space (punctuation); Composite number; Artificial intelligence; Computer science; Machine learning; Operating system; Algorithm","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":[0.000171331,0.0001796438,0.000525666,0.00003945861,0.00003621216,0.000014314,0.0002115174,0.00001493818,0.000002371874],"category_scores_gemma":[0.00001565954,0.000118271,0.0001249804,0.0001465142,0.00003696014,0.0000270468,0.0001014129,0.0004173597,9.221255e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003944007,"about_ca_system_score_gemma":0.00001305387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001012882,"about_ca_topic_score_gemma":0.000004129634,"domain_scores_codex":[0.9992284,0.00009919179,0.0002526229,0.0001473767,0.000165848,0.000106568],"domain_scores_gemma":[0.9993788,0.000107137,0.000172264,0.0002708478,0.00005036183,0.00002057784],"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":[0.000002876628,0.00001003582,0.0001754225,0.04109984,0.00009890871,4.656763e-7,0.0001224853,0.9573103,0.0004896409,0.0001574775,0.00007958005,0.0004530373],"study_design_scores_gemma":[0.0001783161,0.00002191655,0.001202959,0.05423649,0.0006091375,0.000002259169,0.00001687411,0.9392903,0.00292709,0.00001053862,0.001137494,0.0003666425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1984159,0.07955436,0.712868,0.002646768,0.0006577516,0.002553046,0.0001882346,0.0006278887,0.002487978],"genre_scores_gemma":[0.9946069,0.004225236,0.0009112522,0.00009660963,0.00003471794,0.00005032699,0.000044825,0.00001939631,0.00001073358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.796191,"threshold_uncertainty_score":0.4822951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01433020420816181,"score_gpt":0.2358421978035539,"score_spread":0.2215119935953921,"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."}}