{"id":"W2949995719","doi":"10.48550/arxiv.1408.0828","title":"Pre-Reduction Graph Products: Hardnesses of Properly Learning DFAs and Approximating EDP on DAGs","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Combinatorics; Discrete mathematics; Mathematics; Disjoint sets; Deterministic finite automaton; Graph; Algorithm; Finite-state machine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005046852,0.0003164664,0.0004121385,0.0004073731,0.0002844155,0.0001449861,0.00105771,0.0001764452,0.000004540681],"category_scores_gemma":[0.0001332172,0.0003348131,0.0001239557,0.0007158091,0.0002768444,0.0004035023,0.001255178,0.0007506788,0.000005287309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004906549,"about_ca_system_score_gemma":0.0001104692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001150081,"about_ca_topic_score_gemma":0.000003502308,"domain_scores_codex":[0.9978073,0.0002423491,0.0002819161,0.001228913,0.0001515342,0.0002879571],"domain_scores_gemma":[0.9981493,0.00008091579,0.0004847732,0.0009272679,0.0002641625,0.0000935764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001724289,0.0007070473,0.004706946,0.003244763,0.0003472647,0.00006667934,0.005591503,0.4594724,0.00155625,0.490069,0.0002350094,0.03383065],"study_design_scores_gemma":[0.000881149,0.0007499261,0.003169109,0.001253774,0.0001441279,0.00003816712,0.0005277803,0.8636628,0.005252,0.1221301,0.0009426938,0.001248373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6454217,0.00006858311,0.3521442,0.00009523617,0.0006425835,0.0004193549,0.000003777082,0.0002373683,0.0009672068],"genre_scores_gemma":[0.9889256,0.0001031158,0.01020742,0.00001223614,0.0001170511,0.000002225632,0.000009319841,0.00001698786,0.0006060795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4041904,"threshold_uncertainty_score":0.9999104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06393270973561822,"score_gpt":0.1876688978864426,"score_spread":0.1237361881508244,"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."}}