{"id":"W2756975744","doi":"10.37236/5357","title":"Internally Fair Factorizations and Internally Fair Holey Factorizations with Prescribed Regularity","year":2017,"lang":"en","type":"article","venue":"The Electronic Journal of Combinatorics","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Multigraph; Mathematics; Combinatorics; Factorization; Multipartite; Enhanced Data Rates for GSM Evolution; Set (abstract data type); Discrete mathematics; Decomposition; Algorithm; Computer science; Graph","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":[],"consensus_categories":[],"category_scores_codex":[0.0005176801,0.0002171406,0.0003003122,0.0001095339,0.0004204727,0.0002854785,0.0009160118,0.00008706762,0.000008374061],"category_scores_gemma":[0.00009313299,0.0001478141,0.00009434288,0.0001278291,0.0001301097,0.000522156,0.00007096946,0.0007839954,0.000002174842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001668956,"about_ca_system_score_gemma":0.0001280471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001397534,"about_ca_topic_score_gemma":0.0000474272,"domain_scores_codex":[0.9986716,0.00009223245,0.0003957369,0.0001154878,0.00032696,0.0003979815],"domain_scores_gemma":[0.9986646,0.00008262134,0.000388613,0.0004894067,0.0002589762,0.0001158306],"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":[0.000145933,0.0001392058,0.01917462,0.00008632665,0.001034128,0.00002756164,0.002377228,0.001613655,0.003010039,0.9708647,0.0006500934,0.0008765238],"study_design_scores_gemma":[0.006178311,0.002728558,0.08118519,0.000940325,0.0007580914,0.001421896,0.001060465,0.004046972,0.01061055,0.8428078,0.04683654,0.001425327],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.789021,0.001728024,0.2057201,0.0003905286,0.001248827,0.0002224285,0.000008284694,0.00008245317,0.001578328],"genre_scores_gemma":[0.9990733,0.000278485,0.000013973,0.0000118799,0.0001174931,0.000004328475,0.000001708871,0.00003863036,0.0004602319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2100523,"threshold_uncertainty_score":0.6027683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004012664316105553,"score_gpt":0.1815675695086324,"score_spread":0.1775549051925268,"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."}}