{"id":"W4405783345","doi":"10.48550/arxiv.2412.17930","title":"Runs in Paperfolding Sequences","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004298663,0.0004316196,0.0005316153,0.001302418,0.0010426,0.002221671,0.0005487875,0.000764234,0.004687581],"category_scores_gemma":[0.004588191,0.0003917905,0.0006482667,0.0009390151,0.001654449,0.003900743,0.001163808,0.000899467,0.000849022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008303492,"about_ca_system_score_gemma":0.0004448258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008294042,"about_ca_topic_score_gemma":0.0006351065,"domain_scores_codex":[0.9990985,0.0001425707,0.0000858269,0.000370663,0.0001673459,0.0001350864],"domain_scores_gemma":[0.9962302,0.001959732,0.0006169187,0.0004862408,0.0003784194,0.0003285451],"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":[0.0003510889,0.0000782143,0.008130884,0.0002698907,0.00003697568,0.001002582,0.002792761,0.0268798,0.02787747,0.895483,0.001842888,0.03525434],"study_design_scores_gemma":[0.00002950962,0.0001220428,0.003178162,0.00007946727,0.00002828444,0.0005033606,0.0004476803,0.05431442,0.01392527,0.9152458,0.01207031,0.00005559394],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8069561,0.001079997,0.1673444,0.0004249183,0.0001023604,0.00007483506,0.0006841147,0.001012464,0.02232087],"genre_scores_gemma":[0.9662094,0.0003716564,0.02333437,0.0001096123,0.00008663983,0.0001291836,0.0005952673,0.0001977962,0.008966014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004687581,"threshold_uncertainty_score":0.01568151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06660251697708025,"score_gpt":0.1907273914679299,"score_spread":0.1241248744908496,"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."}}