{"id":"W3160769587","doi":"10.48550/arxiv.1708.04640","title":"Lower bounds for graph bootstrap percolation via properties of polynomials","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Hypercube; Simple (philosophy); Torus; Mathematics; Graph; Combinatorics; Set (abstract data type); Percolation (cognitive psychology); Discrete mathematics; Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007822529,0.0003353082,0.0006645974,0.0002344165,0.0002276973,0.00006398101,0.0006596129,0.0004556629,0.00001746357],"category_scores_gemma":[0.0003367909,0.0003379208,0.0005677343,0.00007694196,0.000231528,0.000161409,0.0004076743,0.0002871172,1.762816e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001168054,"about_ca_system_score_gemma":0.0001772988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001688733,"about_ca_topic_score_gemma":0.0001305562,"domain_scores_codex":[0.9985099,0.0001457672,0.0003476654,0.0006174191,0.0000884015,0.0002907976],"domain_scores_gemma":[0.9974445,0.000174767,0.0007201983,0.001194074,0.0003622529,0.0001042402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.008087925,0.003664837,0.008943779,0.02750262,0.005471412,0.0003066183,0.008370084,0.01557845,0.1123803,0.7817779,0.01585224,0.01206377],"study_design_scores_gemma":[0.006200479,0.0009638178,0.0006518277,0.003228089,0.003367326,0.00001446758,0.001373172,0.1122338,0.04177352,0.8178753,0.008640327,0.003677899],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.767912,0.0001374796,0.2263899,0.0000437954,0.0008095737,0.001083553,0.00007524223,0.00007692671,0.003471494],"genre_scores_gemma":[0.9889548,0.0001132521,0.004683313,0.00001460529,0.0001571799,0.000006889421,0.00001373688,0.0000474387,0.00600872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2217066,"threshold_uncertainty_score":0.9999073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2922828317105173,"score_gpt":0.2804926128047923,"score_spread":0.01179021890572507,"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."}}