{"id":"W117982534","doi":"","title":"Inducing regularization of graphs, multigraphs and pseudographs.","year":2002,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"VLSI and FPGA Design Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Regularization (linguistics); Combinatorics; Artificial intelligence; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.000591332,0.0003470398,0.0003348042,0.0008508871,0.0006549369,0.0009900725,0.0006535371,0.0006408051,0.004670442],"category_scores_gemma":[0.003689893,0.0003917206,0.000407831,0.0007620883,0.0009290273,0.001612999,0.001501084,0.001850919,0.0008710361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006919368,"about_ca_system_score_gemma":0.0004753484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005341575,"about_ca_topic_score_gemma":0.002292303,"domain_scores_codex":[0.9993499,0.0002427203,0.0000277403,0.0001329233,0.0002005084,0.00004614558],"domain_scores_gemma":[0.9976245,0.001173279,0.0002747561,0.000520057,0.000254815,0.0001526043],"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":[0.00006568874,0.00006290844,0.0008741359,0.0001674756,0.00002782784,0.0001374593,0.0002279037,0.02467776,0.01066548,0.8628935,0.01063706,0.08956277],"study_design_scores_gemma":[0.00001836789,0.00005694394,0.0008031718,0.00006336502,0.00002313884,0.0003905839,0.0001533946,0.1285232,0.009232201,0.8249036,0.03581084,0.00002120852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07053491,0.0008103974,0.8836663,0.0009538017,0.0001581765,0.00005724179,0.0003051379,0.0007589829,0.04275501],"genre_scores_gemma":[0.5324826,0.001134238,0.4162287,0.0006615369,0.0002594903,0.0001929673,0.0009961434,0.0005733752,0.047471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004670442,"threshold_uncertainty_score":0.01562417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009950917027663106,"score_gpt":0.1897302259514448,"score_spread":0.1797793089237817,"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."}}