{"id":"W2050570613","doi":"10.1145/337244.337257","title":"Learning functions represented as multiplicity automata","year":2000,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Learnability; Mathematics; Discrete mathematics; Multiplicity (mathematics); Disjoint sets; Combinatorics; Computer science; Artificial intelligence","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":[0.0004654249,0.00006569723,0.0001065669,0.00004867202,0.0002383133,0.00007788704,0.002446723,0.00002784036,0.0001909408],"category_scores_gemma":[0.001256596,0.00004001059,0.0001401174,0.0002656621,0.00002189161,0.0002365719,0.0004523717,0.0005487103,0.0001136924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001951309,"about_ca_system_score_gemma":0.00004153665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007064925,"about_ca_topic_score_gemma":9.83056e-7,"domain_scores_codex":[0.9990674,0.0001822338,0.0002166753,0.0001047562,0.0003005928,0.0001282889],"domain_scores_gemma":[0.998597,0.0001061797,0.0002047172,0.0009616336,0.00006710487,0.00006332965],"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":[0.00008236767,0.0003835558,0.03521807,0.00001168812,0.0001891226,0.0001428375,0.004339571,0.06140152,0.00155353,0.0003535369,0.03706713,0.859257],"study_design_scores_gemma":[0.001721352,0.0006832404,0.2088873,0.0001586704,0.00005264183,0.002650516,0.0002164571,0.6010357,0.001366757,0.009028387,0.1738675,0.0003315138],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9512632,0.00008056659,0.01844213,0.01749693,0.00104837,0.00006746977,4.336417e-7,0.0001446274,0.01145624],"genre_scores_gemma":[0.9471633,0.00002231478,0.03342057,0.0003487337,0.0003169806,7.025063e-7,1.490163e-7,0.00000814426,0.01871913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8589256,"threshold_uncertainty_score":0.454666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008940393291089208,"score_gpt":0.2585674569749757,"score_spread":0.2496270636838865,"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."}}