{"id":"W2130384369","doi":"10.1016/j.jda.2012.12.004","title":"A computational framework for determining run-maximal strings","year":2012,"lang":"en","type":"article","venue":"Journal of Discrete Algorithms","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"String (physics); Computation; Combinatorics; Mathematics; Function (biology); Binary number; Key (lock); Element (criminal law); Cover (algebra); Discrete mathematics; Algorithm; Computer science; Arithmetic; Mathematical physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0007169608,0.000175892,0.0003024044,0.0001607811,0.0001928163,0.0002003702,0.0008603407,0.00009585232,0.00001515766],"category_scores_gemma":[0.0001630928,0.0001376841,0.0002110037,0.000215124,0.00003953458,0.002039218,0.0002562929,0.0003055337,0.000007914488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005129328,"about_ca_system_score_gemma":0.0001020275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000254645,"about_ca_topic_score_gemma":7.54528e-8,"domain_scores_codex":[0.9982243,0.00004681047,0.0005646748,0.0001793757,0.0005445332,0.0004403694],"domain_scores_gemma":[0.9981599,0.0004655558,0.0005679344,0.0002587192,0.0002511769,0.0002967237],"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":[0.0001447627,0.000525179,0.004717399,0.00009090997,0.000316117,0.00007555553,0.004105244,0.004321357,0.0003284157,0.1302678,0.006484213,0.848623],"study_design_scores_gemma":[0.00264956,0.001331887,0.01722072,0.0005599849,0.0001001603,0.001127883,0.0003310275,0.8256595,0.00125624,0.1201757,0.02870944,0.0008779303],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00623041,0.0006178223,0.9912537,0.0003862252,0.00128004,0.0001107997,0.00002387931,0.00003041227,0.0000666526],"genre_scores_gemma":[0.2030036,0.00001473922,0.7957119,0.0001692542,0.001060621,0.000004629484,0.000005428158,0.00001352713,0.00001636689],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8477451,"threshold_uncertainty_score":0.5614592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02583056304200663,"score_gpt":0.3077244475159101,"score_spread":0.2818938844739035,"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."}}