{"id":"W1759329419","doi":"10.48550/arxiv.1501.02695","title":"The stripping process can be slow: part I","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Stochastic processes and statistical mechanics","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Monash University","keywords":"Hypergraph; Combinatorics; Vertex (graph theory); Mathematics; Integer (computer science); Stripping (fiber); Constant (computer programming); Degree (music); Physics; Graph; Computer science; Materials science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004778286,0.0003437995,0.0004030115,0.00006517155,0.0003267115,0.0001102139,0.0009596461,0.000292503,0.00003774509],"category_scores_gemma":[0.001717867,0.0002893796,0.0001259409,0.0002978304,0.0001336962,0.00005674243,0.0006701325,0.0007186321,0.00001877351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002175423,"about_ca_system_score_gemma":0.0005823234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004174666,"about_ca_topic_score_gemma":0.0001536833,"domain_scores_codex":[0.9982978,0.00007697412,0.0002886781,0.0006712408,0.0001882512,0.0004770829],"domain_scores_gemma":[0.9973238,0.0007857222,0.0003280602,0.0007805756,0.0005163869,0.0002654487],"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":[0.00006600178,0.00007155644,0.00001955731,0.0003984356,0.000136435,0.0001244488,0.0003812848,0.003452456,0.000001165325,0.9893753,0.005437534,0.0005358242],"study_design_scores_gemma":[0.0003144673,0.00005003243,0.000002288023,0.0001776116,0.0002221345,0.000004153413,0.0009450078,0.09399969,0.0000227889,0.9022937,0.001618631,0.0003495276],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07428626,0.0002321352,0.9102169,0.0006952208,0.001797082,0.001099785,0.0004579493,0.0004211484,0.01079347],"genre_scores_gemma":[0.9953096,0.0001159383,0.000579581,0.00008659786,0.0001851777,0.000005230766,0.00002362806,0.00004670484,0.003647537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9210234,"threshold_uncertainty_score":0.9999558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2078645551788705,"score_gpt":0.2578797381997288,"score_spread":0.05001518302085836,"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."}}