{"id":"W4406780500","doi":"10.48550/arxiv.2501.13044","title":"Uniform temporal trees","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; Natural Sciences and Engineering Research Council of Canada; Banco Bilbao Vizcaya Argentaria; Ministerio de Economía y Competitividad; Fundación BBVA","keywords":"Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001392885,0.0002168324,0.0002329355,0.0001233659,0.0001319261,0.0001430062,0.001934428,0.0001798193,0.00002859289],"category_scores_gemma":[0.00001484933,0.0002099739,0.0001544476,0.0003069256,0.00004423238,0.0001325724,0.002278924,0.0003858756,0.0003271393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005548561,"about_ca_system_score_gemma":0.000267354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002101198,"about_ca_topic_score_gemma":0.00008044878,"domain_scores_codex":[0.9986615,0.00002747,0.0002786655,0.0006175325,0.0001757486,0.0002391105],"domain_scores_gemma":[0.9980063,0.00004581,0.0001312103,0.001673623,0.00006247051,0.00008060896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007726394,0.0007599949,0.5922123,0.000515073,0.0003369364,0.00009806467,0.002105648,0.001135334,0.002033435,0.2757753,0.03763071,0.08738952],"study_design_scores_gemma":[0.0006130264,0.00005264432,0.4281215,0.0003681495,0.00009074071,0.00001516439,0.00006126734,0.08762081,0.009502386,0.02932991,0.442719,0.001505367],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4353438,0.0005774077,0.5183713,0.006018792,0.001357109,0.0006807037,0.00006461164,0.001355124,0.03623119],"genre_scores_gemma":[0.9771914,0.00005234041,0.01256806,0.0003781769,0.0001313344,0.0001159349,0.0001118967,0.000009973818,0.009440907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5418476,"threshold_uncertainty_score":0.8562486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03910676890355345,"score_gpt":0.2783563950166291,"score_spread":0.2392496261130756,"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."}}