{"id":"W2951745001","doi":"10.48550/arxiv.1211.7161","title":"Unshuffling a Square is NP-Hard","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"String (physics); Square (algebra); Interleaving; Combinatorics; Time complexity; Mathematics; Square tiling; Partition (number theory); Reduction (mathematics); Dynamic programming; Discrete mathematics; Computer science; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000229202,0.0003519814,0.0003326078,0.0002138485,0.0002291112,0.0001988744,0.00255037,0.000332858,0.0001353936],"category_scores_gemma":[0.00001443154,0.0003765631,0.0002340088,0.0004344958,0.00006187488,0.0008117277,0.005079052,0.0006709429,0.0004103762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001459526,"about_ca_system_score_gemma":0.0001425718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002069213,"about_ca_topic_score_gemma":0.000005889245,"domain_scores_codex":[0.9979079,0.00009998436,0.0001944294,0.001159703,0.0001430532,0.0004949202],"domain_scores_gemma":[0.9972805,0.00006961051,0.0002419532,0.001985899,0.0001405646,0.0002815159],"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":[0.0001412709,0.00129307,0.0438252,0.001068162,0.000763567,0.001590845,0.005665056,0.1232324,0.0003755242,0.7002799,0.08942237,0.03234268],"study_design_scores_gemma":[0.0007684718,0.00005443256,0.003076274,0.0003508438,0.0001216052,0.00001813521,0.00009378394,0.9045107,0.0004439362,0.03863109,0.05052893,0.001401765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05181351,0.0003069796,0.943736,0.0001984481,0.001341481,0.0002230112,0.00006301901,0.0003758801,0.001941653],"genre_scores_gemma":[0.9829668,0.0001789371,0.01466481,0.0003300937,0.000271896,9.340193e-7,0.00004171529,0.0000227353,0.001522071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9311533,"threshold_uncertainty_score":0.9998686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037334628793013,"score_gpt":0.1964665906088665,"score_spread":0.09273312772956512,"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."}}